{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Probabilistic Modelling Workflow in Turing.jl"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "using Turing, Distributions, Gadfly\n",
    "using Mamba: describe\n",
    "srand(1234)\n",
    ";"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10-element Array{Float64,1}:\n",
       " -4.13265\n",
       " -5.90174\n",
       " -5.49448\n",
       " -5.90291\n",
       " -4.1356 \n",
       "  7.21188\n",
       "  5.53281\n",
       "  4.72826\n",
       "  5.50233\n",
       "  4.48302"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = [(randn(5) .- 5); (randn(5) .+ 5)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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       "\n",
       "]]> </script>\n",
       "<script> <![CDATA[\n",
       "\n",
       "(function (glob, factory) {\n",
       "    // AMD support\n",
       "    if (typeof define === \"function\" && define.amd) {\n",
       "        // Define as an anonymous module\n",
       "        define(\"Gadfly\", [\"Snap.svg\"], function (Snap) {\n",
       "            return factory(Snap);\n",
       "        });\n",
       "    } else {\n",
       "        // Browser globals (glob is window)\n",
       "        // Snap adds itself to window\n",
       "        glob.Gadfly = factory(glob.Snap);\n",
       "    }\n",
       "}(this, function (Snap) {\n",
       "\n",
       "var Gadfly = {};\n",
       "\n",
       "// Get an x/y coordinate value in pixels\n",
       "var xPX = function(fig, x) {\n",
       "    var client_box = fig.node.getBoundingClientRect();\n",
       "    return x * fig.node.viewBox.baseVal.width / client_box.width;\n",
       "};\n",
       "\n",
       "var yPX = function(fig, y) {\n",
       "    var client_box = fig.node.getBoundingClientRect();\n",
       "    return y * fig.node.viewBox.baseVal.height / client_box.height;\n",
       "};\n",
       "\n",
       "\n",
       "Snap.plugin(function (Snap, Element, Paper, global) {\n",
       "    // Traverse upwards from a snap element to find and return the first\n",
       "    // note with the \"plotroot\" class.\n",
       "    Element.prototype.plotroot = function () {\n",
       "        var element = this;\n",
       "        while (!element.hasClass(\"plotroot\") && element.parent() != null) {\n",
       "            element = element.parent();\n",
       "        }\n",
       "        return element;\n",
       "    };\n",
       "\n",
       "    Element.prototype.svgroot = function () {\n",
       "        var element = this;\n",
       "        while (element.node.nodeName != \"svg\" && element.parent() != null) {\n",
       "            element = element.parent();\n",
       "        }\n",
       "        return element;\n",
       "    };\n",
       "\n",
       "    Element.prototype.plotbounds = function () {\n",
       "        var root = this.plotroot()\n",
       "        var bbox = root.select(\".guide.background\").node.getBBox();\n",
       "        return {\n",
       "            x0: bbox.x,\n",
       "            x1: bbox.x + bbox.width,\n",
       "            y0: bbox.y,\n",
       "            y1: bbox.y + bbox.height\n",
       "        };\n",
       "    };\n",
       "\n",
       "    Element.prototype.plotcenter = function () {\n",
       "        var root = this.plotroot()\n",
       "        var bbox = root.select(\".guide.background\").node.getBBox();\n",
       "        return {\n",
       "            x: bbox.x + bbox.width / 2,\n",
       "            y: bbox.y + bbox.height / 2\n",
       "        };\n",
       "    };\n",
       "\n",
       "    // Emulate IE style mouseenter/mouseleave events, since Microsoft always\n",
       "    // does everything right.\n",
       "    // See: http://www.dynamic-tools.net/toolbox/isMouseLeaveOrEnter/\n",
       "    var events = [\"mouseenter\", \"mouseleave\"];\n",
       "\n",
       "    for (i in events) {\n",
       "        (function (event_name) {\n",
       "            var event_name = events[i];\n",
       "            Element.prototype[event_name] = function (fn, scope) {\n",
       "                if (Snap.is(fn, \"function\")) {\n",
       "                    var fn2 = function (event) {\n",
       "                        if (event.type != \"mouseover\" && event.type != \"mouseout\") {\n",
       "                            return;\n",
       "                        }\n",
       "\n",
       "                        var reltg = event.relatedTarget ? event.relatedTarget :\n",
       "                            event.type == \"mouseout\" ? event.toElement : event.fromElement;\n",
       "                        while (reltg && reltg != this.node) reltg = reltg.parentNode;\n",
       "\n",
       "                        if (reltg != this.node) {\n",
       "                            return fn.apply(this, event);\n",
       "                        }\n",
       "                    };\n",
       "\n",
       "                    if (event_name == \"mouseenter\") {\n",
       "                        this.mouseover(fn2, scope);\n",
       "                    } else {\n",
       "                        this.mouseout(fn2, scope);\n",
       "                    }\n",
       "                }\n",
       "                return this;\n",
       "            };\n",
       "        })(events[i]);\n",
       "    }\n",
       "\n",
       "\n",
       "    Element.prototype.mousewheel = function (fn, scope) {\n",
       "        if (Snap.is(fn, \"function\")) {\n",
       "            var el = this;\n",
       "            var fn2 = function (event) {\n",
       "                fn.apply(el, [event]);\n",
       "            };\n",
       "        }\n",
       "\n",
       "        this.node.addEventListener(\n",
       "            /Firefox/i.test(navigator.userAgent) ? \"DOMMouseScroll\" : \"mousewheel\",\n",
       "            fn2);\n",
       "\n",
       "        return this;\n",
       "    };\n",
       "\n",
       "\n",
       "    // Snap's attr function can be too slow for things like panning/zooming.\n",
       "    // This is a function to directly update element attributes without going\n",
       "    // through eve.\n",
       "    Element.prototype.attribute = function(key, val) {\n",
       "        if (val === undefined) {\n",
       "            return this.node.getAttribute(key);\n",
       "        } else {\n",
       "            this.node.setAttribute(key, val);\n",
       "            return this;\n",
       "        }\n",
       "    };\n",
       "\n",
       "    Element.prototype.init_gadfly = function() {\n",
       "        this.mouseenter(Gadfly.plot_mouseover)\n",
       "            .mouseleave(Gadfly.plot_mouseout)\n",
       "            .dblclick(Gadfly.plot_dblclick)\n",
       "            .mousewheel(Gadfly.guide_background_scroll)\n",
       "            .drag(Gadfly.guide_background_drag_onmove,\n",
       "                  Gadfly.guide_background_drag_onstart,\n",
       "                  Gadfly.guide_background_drag_onend);\n",
       "        this.mouseenter(function (event) {\n",
       "            init_pan_zoom(this.plotroot());\n",
       "        });\n",
       "        return this;\n",
       "    };\n",
       "});\n",
       "\n",
       "\n",
       "// When the plot is moused over, emphasize the grid lines.\n",
       "Gadfly.plot_mouseover = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    var keyboard_zoom = function(event) {\n",
       "        if (event.which == 187) { // plus\n",
       "            increase_zoom_by_position(root, 0.1, true);\n",
       "        } else if (event.which == 189) { // minus\n",
       "            increase_zoom_by_position(root, -0.1, true);\n",
       "        }\n",
       "    };\n",
       "    root.data(\"keyboard_zoom\", keyboard_zoom);\n",
       "    window.addEventListener(\"keyup\", keyboard_zoom);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    xgridlines.data(\"unfocused_strokedash\",\n",
       "                    xgridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "    ygridlines.data(\"unfocused_strokedash\",\n",
       "                    ygridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "\n",
       "    // emphasize grid lines\n",
       "    var destcolor = root.data(\"focused_xgrid_color\");\n",
       "    xgridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"focused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // reveal zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 1.0}, 250);\n",
       "};\n",
       "\n",
       "// Reset pan and zoom on double click\n",
       "Gadfly.plot_dblclick = function(event) {\n",
       "  set_plot_pan_zoom(this.plotroot(), 0.0, 0.0, 1.0);\n",
       "};\n",
       "\n",
       "// Unemphasize grid lines on mouse out.\n",
       "Gadfly.plot_mouseout = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    window.removeEventListener(\"keyup\", root.data(\"keyboard_zoom\"));\n",
       "    root.data(\"keyboard_zoom\", undefined);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    var destcolor = root.data(\"unfocused_xgrid_color\");\n",
       "\n",
       "    xgridlines.attribute(\"stroke-dasharray\", xgridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"unfocused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", ygridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // hide zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 0.0}, 250);\n",
       "};\n",
       "\n",
       "\n",
       "var set_geometry_transform = function(root, tx, ty, scale) {\n",
       "    var xscalable = root.hasClass(\"xscalable\"),\n",
       "        yscalable = root.hasClass(\"yscalable\");\n",
       "\n",
       "    var old_scale = root.data(\"scale\");\n",
       "\n",
       "    var xscale = xscalable ? scale : 1.0,\n",
       "        yscale = yscalable ? scale : 1.0;\n",
       "\n",
       "    tx = xscalable ? tx : 0.0;\n",
       "    ty = yscalable ? ty : 0.0;\n",
       "\n",
       "    var t = new Snap.Matrix().translate(tx, ty).scale(xscale, yscale);\n",
       "\n",
       "    root.selectAll(\".geometry, image\")\n",
       "        .forEach(function (element, i) {\n",
       "            element.transform(t);\n",
       "        });\n",
       "\n",
       "    bounds = root.plotbounds();\n",
       "\n",
       "    if (yscalable) {\n",
       "        var xfixed_t = new Snap.Matrix().translate(0, ty).scale(1.0, yscale);\n",
       "        root.selectAll(\".xfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(xfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".ylabels\")\n",
       "            .transform(xfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1, 1/scale, cx, cy).add(st);\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var y = cy * scale + ty;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.y0 <= y && y <= bounds.y1 ? \"visible\" : \"hidden\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (xscalable) {\n",
       "        var yfixed_t = new Snap.Matrix().translate(tx, 0).scale(xscale, 1.0);\n",
       "        var xtrans = new Snap.Matrix().translate(tx, 0);\n",
       "        root.selectAll(\".yfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(yfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".xlabels\")\n",
       "            .transform(yfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1/scale, 1, cx, cy).add(st);\n",
       "\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var x = cx * scale + tx;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.x0 <= x && x <= bounds.x1 ? \"visible\" : \"hidden\");\n",
       "                    }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // we must unscale anything that is scale invariance: widths, raiduses, etc.\n",
       "    var size_attribs = [\"font-size\"];\n",
       "    var unscaled_selection = \".geometry, .geometry *\";\n",
       "    if (xscalable) {\n",
       "        size_attribs.push(\"rx\");\n",
       "        unscaled_selection += \", .xgridlines\";\n",
       "    }\n",
       "    if (yscalable) {\n",
       "        size_attribs.push(\"ry\");\n",
       "        unscaled_selection += \", .ygridlines\";\n",
       "    }\n",
       "\n",
       "    root.selectAll(unscaled_selection)\n",
       "        .forEach(function (element, i) {\n",
       "            // circle need special help\n",
       "            if (element.node.nodeName == \"circle\") {\n",
       "                var cx = element.attribute(\"cx\"),\n",
       "                    cy = element.attribute(\"cy\");\n",
       "                unscale_t = new Snap.Matrix().scale(1/xscale, 1/yscale,\n",
       "                                                        cx, cy);\n",
       "                element.transform(unscale_t);\n",
       "                return;\n",
       "            }\n",
       "\n",
       "            for (i in size_attribs) {\n",
       "                var key = size_attribs[i];\n",
       "                var val = parseFloat(element.attribute(key));\n",
       "                if (val !== undefined && val != 0 && !isNaN(val)) {\n",
       "                    element.attribute(key, val * old_scale / scale);\n",
       "                }\n",
       "            }\n",
       "        });\n",
       "};\n",
       "\n",
       "\n",
       "// Find the most appropriate tick scale and update label visibility.\n",
       "var update_tickscale = function(root, scale, axis) {\n",
       "    if (!root.hasClass(axis + \"scalable\")) return;\n",
       "\n",
       "    var tickscales = root.data(axis + \"tickscales\");\n",
       "    var best_tickscale = 1.0;\n",
       "    var best_tickscale_dist = Infinity;\n",
       "    for (tickscale in tickscales) {\n",
       "        var dist = Math.abs(Math.log(tickscale) - Math.log(scale));\n",
       "        if (dist < best_tickscale_dist) {\n",
       "            best_tickscale_dist = dist;\n",
       "            best_tickscale = tickscale;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    if (best_tickscale != root.data(axis + \"tickscale\")) {\n",
       "        root.data(axis + \"tickscale\", best_tickscale);\n",
       "        var mark_inscale_gridlines = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        var mark_inscale_labels = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        root.select(\".\" + axis + \"gridlines\").selectAll(\"path\").forEach(mark_inscale_gridlines);\n",
       "        root.select(\".\" + axis + \"labels\").selectAll(\"text\").forEach(mark_inscale_labels);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "var set_plot_pan_zoom = function(root, tx, ty, scale) {\n",
       "    var old_scale = root.data(\"scale\");\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    // compute the viewport derived from tx, ty, and scale\n",
       "    var x_min = -width * scale - (scale * width - width),\n",
       "        x_max = width * scale,\n",
       "        y_min = -height * scale - (scale * height - height),\n",
       "        y_max = height * scale;\n",
       "\n",
       "    var x0 = bounds.x0 - scale * bounds.x0,\n",
       "        y0 = bounds.y0 - scale * bounds.y0;\n",
       "\n",
       "    var tx = Math.max(Math.min(tx - x0, x_max), x_min),\n",
       "        ty = Math.max(Math.min(ty - y0, y_max), y_min);\n",
       "\n",
       "    tx += x0;\n",
       "    ty += y0;\n",
       "\n",
       "    // when the scale change, we may need to alter which set of\n",
       "    // ticks is being displayed\n",
       "    if (scale != old_scale) {\n",
       "        update_tickscale(root, scale, \"x\");\n",
       "        update_tickscale(root, scale, \"y\");\n",
       "    }\n",
       "\n",
       "    set_geometry_transform(root, tx, ty, scale);\n",
       "\n",
       "    root.data(\"scale\", scale);\n",
       "    root.data(\"tx\", tx);\n",
       "    root.data(\"ty\", ty);\n",
       "};\n",
       "\n",
       "\n",
       "var scale_centered_translation = function(root, scale) {\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    var tx0 = root.data(\"tx\"),\n",
       "        ty0 = root.data(\"ty\");\n",
       "\n",
       "    var scale0 = root.data(\"scale\");\n",
       "\n",
       "    // how off from center the current view is\n",
       "    var xoff = tx0 - (bounds.x0 * (1 - scale0) + (width * (1 - scale0)) / 2),\n",
       "        yoff = ty0 - (bounds.y0 * (1 - scale0) + (height * (1 - scale0)) / 2);\n",
       "\n",
       "    // rescale offsets\n",
       "    xoff = xoff * scale / scale0;\n",
       "    yoff = yoff * scale / scale0;\n",
       "\n",
       "    // adjust for the panel position being scaled\n",
       "    var x_edge_adjust = bounds.x0 * (1 - scale),\n",
       "        y_edge_adjust = bounds.y0 * (1 - scale);\n",
       "\n",
       "    return {\n",
       "        x: xoff + x_edge_adjust + (width - width * scale) / 2,\n",
       "        y: yoff + y_edge_adjust + (height - height * scale) / 2\n",
       "    };\n",
       "};\n",
       "\n",
       "\n",
       "// Initialize data for panning zooming if it isn't already.\n",
       "var init_pan_zoom = function(root) {\n",
       "    if (root.data(\"zoompan-ready\")) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    // The non-scaling-stroke trick. Rather than try to correct for the\n",
       "    // stroke-width when zooming, we force it to a fixed value.\n",
       "    var px_per_mm = root.node.getCTM().a;\n",
       "\n",
       "    // Drag events report deltas in pixels, which we'd like to convert to\n",
       "    // millimeters.\n",
       "    root.data(\"px_per_mm\", px_per_mm);\n",
       "\n",
       "    root.selectAll(\"path\")\n",
       "        .forEach(function (element, i) {\n",
       "        sw = element.asPX(\"stroke-width\") * px_per_mm;\n",
       "        if (sw > 0) {\n",
       "            element.attribute(\"stroke-width\", sw);\n",
       "            element.attribute(\"vector-effect\", \"non-scaling-stroke\");\n",
       "        }\n",
       "    });\n",
       "\n",
       "    // Store ticks labels original tranformation\n",
       "    root.selectAll(\".xlabels > text, .ylabels > text\")\n",
       "        .forEach(function (element, i) {\n",
       "            var lm = element.transform().localMatrix;\n",
       "            element.data(\"static_transform\",\n",
       "                new Snap.Matrix(lm.a, lm.b, lm.c, lm.d, lm.e, lm.f));\n",
       "        });\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\");\n",
       "    var ygridlines = root.select(\".ygridlines\");\n",
       "    var xlabels = root.select(\".xlabels\");\n",
       "    var ylabels = root.select(\".ylabels\");\n",
       "\n",
       "    if (root.data(\"tx\") === undefined) root.data(\"tx\", 0);\n",
       "    if (root.data(\"ty\") === undefined) root.data(\"ty\", 0);\n",
       "    if (root.data(\"scale\") === undefined) root.data(\"scale\", 1.0);\n",
       "    if (root.data(\"xtickscales\") === undefined) {\n",
       "\n",
       "        // index all the tick scales that are listed\n",
       "        var xtickscales = {};\n",
       "        var ytickscales = {};\n",
       "        var add_x_tick_scales = function (element, i) {\n",
       "            xtickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "        var add_y_tick_scales = function (element, i) {\n",
       "            ytickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "\n",
       "        if (xgridlines) xgridlines.selectAll(\"path\").forEach(add_x_tick_scales);\n",
       "        if (ygridlines) ygridlines.selectAll(\"path\").forEach(add_y_tick_scales);\n",
       "        if (xlabels) xlabels.selectAll(\"text\").forEach(add_x_tick_scales);\n",
       "        if (ylabels) ylabels.selectAll(\"text\").forEach(add_y_tick_scales);\n",
       "\n",
       "        root.data(\"xtickscales\", xtickscales);\n",
       "        root.data(\"ytickscales\", ytickscales);\n",
       "        root.data(\"xtickscale\", 1.0);\n",
       "    }\n",
       "\n",
       "    var min_scale = 1.0, max_scale = 1.0;\n",
       "    for (scale in xtickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    for (scale in ytickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    root.data(\"min_scale\", min_scale);\n",
       "    root.data(\"max_scale\", max_scale);\n",
       "\n",
       "    // store the original positions of labels\n",
       "    if (xlabels) {\n",
       "        xlabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"x\", element.asPX(\"x\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    if (ylabels) {\n",
       "        ylabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"y\", element.asPX(\"y\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    // mark grid lines and ticks as in or out of scale.\n",
       "    var mark_inscale = function (element, i) {\n",
       "        element.attribute(\"gadfly:inscale\", element.attribute(\"gadfly:scale\") == 1.0);\n",
       "    };\n",
       "\n",
       "    if (xgridlines) xgridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (ygridlines) ygridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (xlabels) xlabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "    if (ylabels) ylabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "\n",
       "    // figure out the upper ond lower bounds on panning using the maximum\n",
       "    // and minum grid lines\n",
       "    var bounds = root.plotbounds();\n",
       "    var pan_bounds = {\n",
       "        x0: 0.0,\n",
       "        y0: 0.0,\n",
       "        x1: 0.0,\n",
       "        y1: 0.0\n",
       "    };\n",
       "\n",
       "    if (xgridlines) {\n",
       "        xgridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.x1 - bbox.x < pan_bounds.x0) {\n",
       "                        pan_bounds.x0 = bounds.x1 - bbox.x;\n",
       "                    }\n",
       "                    if (bounds.x0 - bbox.x > pan_bounds.x1) {\n",
       "                        pan_bounds.x1 = bounds.x0 - bbox.x;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (ygridlines) {\n",
       "        ygridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.y1 - bbox.y < pan_bounds.y0) {\n",
       "                        pan_bounds.y0 = bounds.y1 - bbox.y;\n",
       "                    }\n",
       "                    if (bounds.y0 - bbox.y > pan_bounds.y1) {\n",
       "                        pan_bounds.y1 = bounds.y0 - bbox.y;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // nudge these values a little\n",
       "    pan_bounds.x0 -= 5;\n",
       "    pan_bounds.x1 += 5;\n",
       "    pan_bounds.y0 -= 5;\n",
       "    pan_bounds.y1 += 5;\n",
       "    root.data(\"pan_bounds\", pan_bounds);\n",
       "\n",
       "    root.data(\"zoompan-ready\", true)\n",
       "};\n",
       "\n",
       "\n",
       "// drag actions, i.e. zooming and panning\n",
       "var pan_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        root.data(\"dx\", 0);\n",
       "        root.data(\"dy\", 0);\n",
       "        root.data(\"tx0\", root.data(\"tx\"));\n",
       "        root.data(\"ty0\", root.data(\"ty\"));\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        dx /= px_per_mm;\n",
       "        dy /= px_per_mm;\n",
       "\n",
       "        var tx0 = root.data(\"tx\"),\n",
       "            ty0 = root.data(\"ty\");\n",
       "\n",
       "        var dx0 = root.data(\"dx\"),\n",
       "            dy0 = root.data(\"dy\");\n",
       "\n",
       "        root.data(\"dx\", dx);\n",
       "        root.data(\"dy\", dy);\n",
       "\n",
       "        dx = dx - dx0;\n",
       "        dy = dy - dy0;\n",
       "\n",
       "        var tx = tx0 + dx,\n",
       "            ty = ty0 + dy;\n",
       "\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\"));\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        set_plot_pan_zoom(root, root.data(\"tx0\"), root.data(\"ty0\"), root.data(\"scale\"));\n",
       "    }\n",
       "};\n",
       "\n",
       "var zoom_box;\n",
       "var zoom_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        var bounds = root.plotbounds();\n",
       "        var width = bounds.x1 - bounds.x0,\n",
       "            height = bounds.y1 - bounds.y0;\n",
       "        var ratio = width / height;\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        x = xscalable ? x / px_per_mm : bounds.x0;\n",
       "        y = yscalable ? y / px_per_mm : bounds.y0;\n",
       "        var w = xscalable ? 0 : width;\n",
       "        var h = yscalable ? 0 : height;\n",
       "        zoom_box = root.rect(x, y, w, h).attr({\n",
       "            \"fill\": \"#000\",\n",
       "            \"opacity\": 0.25\n",
       "        });\n",
       "        zoom_box.data(\"ratio\", ratio);\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        var bounds = root.plotbounds();\n",
       "        if (yscalable) {\n",
       "            y /= px_per_mm;\n",
       "            y = Math.max(bounds.y0, y);\n",
       "            y = Math.min(bounds.y1, y);\n",
       "        } else {\n",
       "            y = bounds.y1;\n",
       "        }\n",
       "        if (xscalable) {\n",
       "            x /= px_per_mm;\n",
       "            x = Math.max(bounds.x0, x);\n",
       "            x = Math.min(bounds.x1, x);\n",
       "        } else {\n",
       "            x = bounds.x1;\n",
       "        }\n",
       "\n",
       "        dx = x - zoom_box.attr(\"x\");\n",
       "        dy = y - zoom_box.attr(\"y\");\n",
       "        if (xscalable && yscalable) {\n",
       "            var ratio = zoom_box.data(\"ratio\");\n",
       "            var width = Math.min(Math.abs(dx), ratio * Math.abs(dy));\n",
       "            var height = Math.min(Math.abs(dy), Math.abs(dx) / ratio);\n",
       "            dx = width * dx / Math.abs(dx);\n",
       "            dy = height * dy / Math.abs(dy);\n",
       "        }\n",
       "        var xoffset = 0,\n",
       "            yoffset = 0;\n",
       "        if (dx < 0) {\n",
       "            xoffset = dx;\n",
       "            dx = -1 * dx;\n",
       "        }\n",
       "        if (dy < 0) {\n",
       "            yoffset = dy;\n",
       "            dy = -1 * dy;\n",
       "        }\n",
       "        if (isNaN(dy)) {\n",
       "            dy = 0.0;\n",
       "        }\n",
       "        if (isNaN(dx)) {\n",
       "            dx = 0.0;\n",
       "        }\n",
       "        zoom_box.transform(\"T\" + xoffset + \",\" + yoffset);\n",
       "        zoom_box.attr(\"width\", dx);\n",
       "        zoom_box.attr(\"height\", dy);\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var zoom_bounds = zoom_box.getBBox();\n",
       "        if (zoom_bounds.width * zoom_bounds.height <= 0) {\n",
       "            return;\n",
       "        }\n",
       "        var plot_bounds = root.plotbounds();\n",
       "        var zoom_factor = 1.0;\n",
       "        if (yscalable) {\n",
       "            zoom_factor = (plot_bounds.y1 - plot_bounds.y0) / zoom_bounds.height;\n",
       "        } else {\n",
       "            zoom_factor = (plot_bounds.x1 - plot_bounds.x0) / zoom_bounds.width;\n",
       "        }\n",
       "        var tx = (root.data(\"tx\") - zoom_bounds.x) * zoom_factor + plot_bounds.x0,\n",
       "            ty = (root.data(\"ty\") - zoom_bounds.y) * zoom_factor + plot_bounds.y0;\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\") * zoom_factor);\n",
       "        zoom_box.remove();\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        zoom_box.remove();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onstart = function(x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var scalable = root.hasClass(\"xscalable\") || root.hasClass(\"yscalable\");\n",
       "    var zoomable = !event.altKey && !event.ctrlKey && event.shiftKey && scalable;\n",
       "    var panable = !event.altKey && !event.ctrlKey && !event.shiftKey && scalable;\n",
       "    var drag_action = zoomable ? zoom_action :\n",
       "                      panable  ? pan_action :\n",
       "                                 undefined;\n",
       "    root.data(\"drag_action\", drag_action);\n",
       "    if (drag_action) {\n",
       "        var cancel_drag_action = function(event) {\n",
       "            if (event.which == 27) { // esc key\n",
       "                drag_action.cancel(root);\n",
       "                root.data(\"drag_action\", undefined);\n",
       "            }\n",
       "        };\n",
       "        window.addEventListener(\"keyup\", cancel_drag_action);\n",
       "        root.data(\"cancel_drag_action\", cancel_drag_action);\n",
       "        drag_action.start(root, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.update(root, dx, dy, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onend = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    window.removeEventListener(\"keyup\", root.data(\"cancel_drag_action\"));\n",
       "    root.data(\"cancel_drag_action\", undefined);\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.end(root, event);\n",
       "    }\n",
       "    root.data(\"drag_action\", undefined);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_scroll = function(event) {\n",
       "    if (event.shiftKey) {\n",
       "        increase_zoom_by_position(this.plotroot(), 0.001 * event.wheelDelta);\n",
       "        event.preventDefault();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseover = function(event) {\n",
       "    this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseout = function(event) {\n",
       "     this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomout_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), -0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomin_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), 0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_track_click = function(event) {\n",
       "    // TODO\n",
       "};\n",
       "\n",
       "\n",
       "// Map slider position x to scale y using the function y = a*exp(b*x)+c.\n",
       "// The constants a, b, and c are solved using the constraint that the function\n",
       "// should go through the points (0; min_scale), (0.5; 1), and (1; max_scale).\n",
       "var scale_from_slider_position = function(position, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return a * Math.exp(b * position) + c;\n",
       "}\n",
       "\n",
       "// inverse of scale_from_slider_position\n",
       "var slider_position_from_scale = function(scale, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return 1 / b * Math.log((scale - c) / a);\n",
       "}\n",
       "\n",
       "var increase_zoom_by_position = function(root, delta_position, animate) {\n",
       "    var scale = root.data(\"scale\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\");\n",
       "    var position = slider_position_from_scale(scale, min_scale, max_scale);\n",
       "    position += delta_position;\n",
       "    scale = scale_from_slider_position(position, min_scale, max_scale);\n",
       "    set_zoom(root, scale, animate);\n",
       "}\n",
       "\n",
       "var set_zoom = function(root, scale, animate) {\n",
       "    var min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"scale\");\n",
       "    var new_scale = Math.max(min_scale, Math.min(scale, max_scale));\n",
       "    if (animate) {\n",
       "        Snap.animate(\n",
       "            old_scale,\n",
       "            new_scale,\n",
       "            function (new_scale) {\n",
       "                update_plot_scale(root, new_scale);\n",
       "            },\n",
       "            200);\n",
       "    } else {\n",
       "        update_plot_scale(root, new_scale);\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "var update_plot_scale = function(root, new_scale) {\n",
       "    var trans = scale_centered_translation(root, new_scale);\n",
       "    set_plot_pan_zoom(root, trans.x, trans.y, new_scale);\n",
       "\n",
       "    root.selectAll(\".zoomslider_thumb\")\n",
       "        .forEach(function (element, i) {\n",
       "            var min_pos = element.data(\"min_pos\"),\n",
       "                max_pos = element.data(\"max_pos\"),\n",
       "                min_scale = root.data(\"min_scale\"),\n",
       "                max_scale = root.data(\"max_scale\");\n",
       "            var xmid = (min_pos + max_pos) / 2;\n",
       "            var xpos = slider_position_from_scale(new_scale, min_scale, max_scale);\n",
       "            element.transform(new Snap.Matrix().translate(\n",
       "                Math.max(min_pos, Math.min(\n",
       "                         max_pos, min_pos + (max_pos - min_pos) * xpos)) - xmid, 0));\n",
       "    });\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var min_pos = this.data(\"min_pos\"),\n",
       "        max_pos = this.data(\"max_pos\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"old_scale\");\n",
       "\n",
       "    var px_per_mm = root.data(\"px_per_mm\");\n",
       "    dx /= px_per_mm;\n",
       "    dy /= px_per_mm;\n",
       "\n",
       "    var xmid = (min_pos + max_pos) / 2;\n",
       "    var xpos = slider_position_from_scale(old_scale, min_scale, max_scale) +\n",
       "                   dx / (max_pos - min_pos);\n",
       "\n",
       "    // compute the new scale\n",
       "    var new_scale = scale_from_slider_position(xpos, min_scale, max_scale);\n",
       "    new_scale = Math.min(max_scale, Math.max(min_scale, new_scale));\n",
       "\n",
       "    update_plot_scale(root, new_scale);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragstart = function(x, y, event) {\n",
       "    this.animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    // keep track of what the scale was when we started dragging\n",
       "    root.data(\"old_scale\", root.data(\"scale\"));\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragend = function(event) {\n",
       "    this.animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "var toggle_color_class = function(root, color_class, ison) {\n",
       "    var guides = root.selectAll(\".guide.\" + color_class + \",.guide .\" + color_class);\n",
       "    var geoms = root.selectAll(\".geometry.\" + color_class + \",.geometry .\" + color_class);\n",
       "    if (ison) {\n",
       "        guides.animate({opacity: 0.5}, 250);\n",
       "        geoms.animate({opacity: 0.0}, 250);\n",
       "    } else {\n",
       "        guides.animate({opacity: 1.0}, 250);\n",
       "        geoms.animate({opacity: 1.0}, 250);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.colorkey_swatch_click = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    var color_class = this.data(\"color_class\");\n",
       "\n",
       "    if (event.shiftKey) {\n",
       "        root.selectAll(\".colorkey text\")\n",
       "            .forEach(function (element) {\n",
       "                var other_color_class = element.data(\"color_class\");\n",
       "                if (other_color_class != color_class) {\n",
       "                    toggle_color_class(root, other_color_class,\n",
       "                                       element.attr(\"opacity\") == 1.0);\n",
       "                }\n",
       "            });\n",
       "    } else {\n",
       "        toggle_color_class(root, color_class, this.attr(\"opacity\") == 1.0);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "return Gadfly;\n",
       "\n",
       "}));\n",
       "\n",
       "\n",
       "//@ sourceURL=gadfly.js\n",
       "\n",
       "(function (glob, factory) {\n",
       "    // AMD support\n",
       "      if (typeof require === \"function\" && typeof define === \"function\" && define.amd) {\n",
       "        require([\"Snap.svg\", \"Gadfly\"], function (Snap, Gadfly) {\n",
       "            factory(Snap, Gadfly);\n",
       "        });\n",
       "      } else {\n",
       "          factory(glob.Snap, glob.Gadfly);\n",
       "      }\n",
       "})(window, function (Snap, Gadfly) {\n",
       "    var fig = Snap(\"#img-9d700c96\");\n",
       "fig.select(\"#img-9d700c96-5\")\n",
       "   .init_gadfly();\n",
       "fig.select(\"#img-9d700c96-7\")\n",
       "   .plotroot().data(\"unfocused_ygrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-9d700c96-7\")\n",
       "   .plotroot().data(\"focused_ygrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-9d700c96-8\")\n",
       "   .plotroot().data(\"unfocused_xgrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-9d700c96-8\")\n",
       "   .plotroot().data(\"focused_xgrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-9d700c96-33\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-9d700c96-33\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-9d700c96-33\")\n",
       "   .click(Gadfly.zoomslider_zoomin_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "fig.select(\"#img-9d700c96-35\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-9d700c96-35\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-9d700c96-35\")\n",
       "   .click(Gadfly.zoomslider_track_click);\n",
       "fig.select(\"#img-9d700c96-36\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-9d700c96-36\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-9d700c96-36\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-9d700c96-36\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-9d700c96-36\")\n",
       "   .drag(Gadfly.zoomslider_thumb_dragmove,\n",
       "     Gadfly.zoomslider_thumb_dragstart,\n",
       "     Gadfly.zoomslider_thumb_dragend)\n",
       ";\n",
       "fig.select(\"#img-9d700c96-37\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-9d700c96-37\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-9d700c96-37\")\n",
       "   .click(Gadfly.zoomslider_zoomout_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "    });\n",
       "]]> </script>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "Plot(...)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l_x = layer(x=x, y=zeros(length(x)), Geom.point)\n",
    "plot(l_x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define a very simple Gaussian model\n",
    "$$ \\mu \\sim \\textit{Normal}(0, 100) $$\n",
    "$$ x_i \\sim \\textit{Normal}(\\mu, 1), i = 1 \\dots N $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "g_simple (generic function with 2 methods)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "@model g_simple(x) = begin\n",
    "    m ~ Normal(0, 100)\n",
    "    for i = 1:length(x)\n",
    "        x[i] ~ Normal(m, 1)\n",
    "    end\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Inference by Markov Chain Monte Carlo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Turing]:  Assume - `m` is a parameter\n",
      "  in @~(::Any, ::Any) at compiler.jl:56\n",
      "[Turing]:  Observe - `x` is an observation\n",
      "  in @~(::Any, ::Any) at compiler.jl:35\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "[HMC] Sampling...  0%  ETA: 0:14:08\r",
      "[HMC] Sampling... 28%  ETA: 0:00:07"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[HMC] Finished with\n",
      "  Running time        = 5.033370767;\n",
      "  Accept rate         = 0.001;\n",
      "  #lf / sample        = 9.99;\n",
      "  #evals / sample     = 9.992;\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "[HMC] Sampling... 58%  ETA: 0:00:03\r",
      "[HMC] Sampling... 86%  ETA: 0:00:01\r",
      "[HMC] Sampling...100% Time: 0:00:05\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  pre-cond. diag mat  = [1.0].\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Object of type \"Turing.Chain\"\n",
       "\n",
       "Iterations = 1:1000\n",
       "Thinning interval = 1\n",
       "Chains = 1\n",
       "Samples per chain = 1000\n",
       "\n",
       "[0.750303 -160.809 0.0 0.00351025; 0.750303 -160.809 0.0 0.00351025; … ; 0.750303 -160.809 0.0 0.00351025; 0.750303 -160.809 0.0 0.00351025]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chn1 = sample(g_simple(x), HMC(1000, 1.5, 10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Check the statistics of the result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iterations = 1:1000\n",
      "Thinning interval = 1\n",
      "Chains = 1\n",
      "Samples per chain = 1000\n",
      "\n",
      "Empirical Posterior Estimates:\n",
      "             Mean                      SD                              Naive SE                           MCSE                  ESS   \n",
      "      m    0.750302734   4.22095850070973721557266×10⁻¹⁵    1.334784277129221763402711×10⁻¹⁶                              0 1000.00000\n",
      "     lp -160.809070517     1.421796547607490301957×10⁻¹³     4.49611545980369431418922×10⁻¹⁵ 9.4739031434680036625195×10⁻¹⁵  225.22523\n",
      " lf_num    0.000000000                                 0                                   0                              0 1000.00000\n",
      "elapsed    0.003510246 1.8657608504370750690526393×10⁻¹⁷ 5.900053856553920894612019765×10⁻¹⁹                              0 1000.00000\n",
      "\n",
      "Quantiles:\n",
      "             2.5%           25.0%          50.0%          75.0%          97.5%    \n",
      "      m    0.750302734    0.750302734    0.750302734    0.750302734    0.750302734\n",
      "     lp -160.809070517 -160.809070517 -160.809070517 -160.809070517 -160.809070517\n",
      " lf_num    0.000000000    0.000000000    0.000000000    0.000000000    0.000000000\n",
      "elapsed    0.003510246    0.003510246    0.003510246    0.003510246    0.003510246\n",
      "\n"
     ]
    }
   ],
   "source": [
    "describe(chn1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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       "                        this.mouseover(fn2, scope);\n",
       "                    } else {\n",
       "                        this.mouseout(fn2, scope);\n",
       "                    }\n",
       "                }\n",
       "                return this;\n",
       "            };\n",
       "        })(events[i]);\n",
       "    }\n",
       "\n",
       "\n",
       "    Element.prototype.mousewheel = function (fn, scope) {\n",
       "        if (Snap.is(fn, \"function\")) {\n",
       "            var el = this;\n",
       "            var fn2 = function (event) {\n",
       "                fn.apply(el, [event]);\n",
       "            };\n",
       "        }\n",
       "\n",
       "        this.node.addEventListener(\n",
       "            /Firefox/i.test(navigator.userAgent) ? \"DOMMouseScroll\" : \"mousewheel\",\n",
       "            fn2);\n",
       "\n",
       "        return this;\n",
       "    };\n",
       "\n",
       "\n",
       "    // Snap's attr function can be too slow for things like panning/zooming.\n",
       "    // This is a function to directly update element attributes without going\n",
       "    // through eve.\n",
       "    Element.prototype.attribute = function(key, val) {\n",
       "        if (val === undefined) {\n",
       "            return this.node.getAttribute(key);\n",
       "        } else {\n",
       "            this.node.setAttribute(key, val);\n",
       "            return this;\n",
       "        }\n",
       "    };\n",
       "\n",
       "    Element.prototype.init_gadfly = function() {\n",
       "        this.mouseenter(Gadfly.plot_mouseover)\n",
       "            .mouseleave(Gadfly.plot_mouseout)\n",
       "            .dblclick(Gadfly.plot_dblclick)\n",
       "            .mousewheel(Gadfly.guide_background_scroll)\n",
       "            .drag(Gadfly.guide_background_drag_onmove,\n",
       "                  Gadfly.guide_background_drag_onstart,\n",
       "                  Gadfly.guide_background_drag_onend);\n",
       "        this.mouseenter(function (event) {\n",
       "            init_pan_zoom(this.plotroot());\n",
       "        });\n",
       "        return this;\n",
       "    };\n",
       "});\n",
       "\n",
       "\n",
       "// When the plot is moused over, emphasize the grid lines.\n",
       "Gadfly.plot_mouseover = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    var keyboard_zoom = function(event) {\n",
       "        if (event.which == 187) { // plus\n",
       "            increase_zoom_by_position(root, 0.1, true);\n",
       "        } else if (event.which == 189) { // minus\n",
       "            increase_zoom_by_position(root, -0.1, true);\n",
       "        }\n",
       "    };\n",
       "    root.data(\"keyboard_zoom\", keyboard_zoom);\n",
       "    window.addEventListener(\"keyup\", keyboard_zoom);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    xgridlines.data(\"unfocused_strokedash\",\n",
       "                    xgridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "    ygridlines.data(\"unfocused_strokedash\",\n",
       "                    ygridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "\n",
       "    // emphasize grid lines\n",
       "    var destcolor = root.data(\"focused_xgrid_color\");\n",
       "    xgridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"focused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // reveal zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 1.0}, 250);\n",
       "};\n",
       "\n",
       "// Reset pan and zoom on double click\n",
       "Gadfly.plot_dblclick = function(event) {\n",
       "  set_plot_pan_zoom(this.plotroot(), 0.0, 0.0, 1.0);\n",
       "};\n",
       "\n",
       "// Unemphasize grid lines on mouse out.\n",
       "Gadfly.plot_mouseout = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    window.removeEventListener(\"keyup\", root.data(\"keyboard_zoom\"));\n",
       "    root.data(\"keyboard_zoom\", undefined);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    var destcolor = root.data(\"unfocused_xgrid_color\");\n",
       "\n",
       "    xgridlines.attribute(\"stroke-dasharray\", xgridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"unfocused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", ygridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // hide zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 0.0}, 250);\n",
       "};\n",
       "\n",
       "\n",
       "var set_geometry_transform = function(root, tx, ty, scale) {\n",
       "    var xscalable = root.hasClass(\"xscalable\"),\n",
       "        yscalable = root.hasClass(\"yscalable\");\n",
       "\n",
       "    var old_scale = root.data(\"scale\");\n",
       "\n",
       "    var xscale = xscalable ? scale : 1.0,\n",
       "        yscale = yscalable ? scale : 1.0;\n",
       "\n",
       "    tx = xscalable ? tx : 0.0;\n",
       "    ty = yscalable ? ty : 0.0;\n",
       "\n",
       "    var t = new Snap.Matrix().translate(tx, ty).scale(xscale, yscale);\n",
       "\n",
       "    root.selectAll(\".geometry, image\")\n",
       "        .forEach(function (element, i) {\n",
       "            element.transform(t);\n",
       "        });\n",
       "\n",
       "    bounds = root.plotbounds();\n",
       "\n",
       "    if (yscalable) {\n",
       "        var xfixed_t = new Snap.Matrix().translate(0, ty).scale(1.0, yscale);\n",
       "        root.selectAll(\".xfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(xfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".ylabels\")\n",
       "            .transform(xfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1, 1/scale, cx, cy).add(st);\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var y = cy * scale + ty;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.y0 <= y && y <= bounds.y1 ? \"visible\" : \"hidden\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (xscalable) {\n",
       "        var yfixed_t = new Snap.Matrix().translate(tx, 0).scale(xscale, 1.0);\n",
       "        var xtrans = new Snap.Matrix().translate(tx, 0);\n",
       "        root.selectAll(\".yfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(yfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".xlabels\")\n",
       "            .transform(yfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1/scale, 1, cx, cy).add(st);\n",
       "\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var x = cx * scale + tx;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.x0 <= x && x <= bounds.x1 ? \"visible\" : \"hidden\");\n",
       "                    }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // we must unscale anything that is scale invariance: widths, raiduses, etc.\n",
       "    var size_attribs = [\"font-size\"];\n",
       "    var unscaled_selection = \".geometry, .geometry *\";\n",
       "    if (xscalable) {\n",
       "        size_attribs.push(\"rx\");\n",
       "        unscaled_selection += \", .xgridlines\";\n",
       "    }\n",
       "    if (yscalable) {\n",
       "        size_attribs.push(\"ry\");\n",
       "        unscaled_selection += \", .ygridlines\";\n",
       "    }\n",
       "\n",
       "    root.selectAll(unscaled_selection)\n",
       "        .forEach(function (element, i) {\n",
       "            // circle need special help\n",
       "            if (element.node.nodeName == \"circle\") {\n",
       "                var cx = element.attribute(\"cx\"),\n",
       "                    cy = element.attribute(\"cy\");\n",
       "                unscale_t = new Snap.Matrix().scale(1/xscale, 1/yscale,\n",
       "                                                        cx, cy);\n",
       "                element.transform(unscale_t);\n",
       "                return;\n",
       "            }\n",
       "\n",
       "            for (i in size_attribs) {\n",
       "                var key = size_attribs[i];\n",
       "                var val = parseFloat(element.attribute(key));\n",
       "                if (val !== undefined && val != 0 && !isNaN(val)) {\n",
       "                    element.attribute(key, val * old_scale / scale);\n",
       "                }\n",
       "            }\n",
       "        });\n",
       "};\n",
       "\n",
       "\n",
       "// Find the most appropriate tick scale and update label visibility.\n",
       "var update_tickscale = function(root, scale, axis) {\n",
       "    if (!root.hasClass(axis + \"scalable\")) return;\n",
       "\n",
       "    var tickscales = root.data(axis + \"tickscales\");\n",
       "    var best_tickscale = 1.0;\n",
       "    var best_tickscale_dist = Infinity;\n",
       "    for (tickscale in tickscales) {\n",
       "        var dist = Math.abs(Math.log(tickscale) - Math.log(scale));\n",
       "        if (dist < best_tickscale_dist) {\n",
       "            best_tickscale_dist = dist;\n",
       "            best_tickscale = tickscale;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    if (best_tickscale != root.data(axis + \"tickscale\")) {\n",
       "        root.data(axis + \"tickscale\", best_tickscale);\n",
       "        var mark_inscale_gridlines = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        var mark_inscale_labels = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        root.select(\".\" + axis + \"gridlines\").selectAll(\"path\").forEach(mark_inscale_gridlines);\n",
       "        root.select(\".\" + axis + \"labels\").selectAll(\"text\").forEach(mark_inscale_labels);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "var set_plot_pan_zoom = function(root, tx, ty, scale) {\n",
       "    var old_scale = root.data(\"scale\");\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    // compute the viewport derived from tx, ty, and scale\n",
       "    var x_min = -width * scale - (scale * width - width),\n",
       "        x_max = width * scale,\n",
       "        y_min = -height * scale - (scale * height - height),\n",
       "        y_max = height * scale;\n",
       "\n",
       "    var x0 = bounds.x0 - scale * bounds.x0,\n",
       "        y0 = bounds.y0 - scale * bounds.y0;\n",
       "\n",
       "    var tx = Math.max(Math.min(tx - x0, x_max), x_min),\n",
       "        ty = Math.max(Math.min(ty - y0, y_max), y_min);\n",
       "\n",
       "    tx += x0;\n",
       "    ty += y0;\n",
       "\n",
       "    // when the scale change, we may need to alter which set of\n",
       "    // ticks is being displayed\n",
       "    if (scale != old_scale) {\n",
       "        update_tickscale(root, scale, \"x\");\n",
       "        update_tickscale(root, scale, \"y\");\n",
       "    }\n",
       "\n",
       "    set_geometry_transform(root, tx, ty, scale);\n",
       "\n",
       "    root.data(\"scale\", scale);\n",
       "    root.data(\"tx\", tx);\n",
       "    root.data(\"ty\", ty);\n",
       "};\n",
       "\n",
       "\n",
       "var scale_centered_translation = function(root, scale) {\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    var tx0 = root.data(\"tx\"),\n",
       "        ty0 = root.data(\"ty\");\n",
       "\n",
       "    var scale0 = root.data(\"scale\");\n",
       "\n",
       "    // how off from center the current view is\n",
       "    var xoff = tx0 - (bounds.x0 * (1 - scale0) + (width * (1 - scale0)) / 2),\n",
       "        yoff = ty0 - (bounds.y0 * (1 - scale0) + (height * (1 - scale0)) / 2);\n",
       "\n",
       "    // rescale offsets\n",
       "    xoff = xoff * scale / scale0;\n",
       "    yoff = yoff * scale / scale0;\n",
       "\n",
       "    // adjust for the panel position being scaled\n",
       "    var x_edge_adjust = bounds.x0 * (1 - scale),\n",
       "        y_edge_adjust = bounds.y0 * (1 - scale);\n",
       "\n",
       "    return {\n",
       "        x: xoff + x_edge_adjust + (width - width * scale) / 2,\n",
       "        y: yoff + y_edge_adjust + (height - height * scale) / 2\n",
       "    };\n",
       "};\n",
       "\n",
       "\n",
       "// Initialize data for panning zooming if it isn't already.\n",
       "var init_pan_zoom = function(root) {\n",
       "    if (root.data(\"zoompan-ready\")) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    // The non-scaling-stroke trick. Rather than try to correct for the\n",
       "    // stroke-width when zooming, we force it to a fixed value.\n",
       "    var px_per_mm = root.node.getCTM().a;\n",
       "\n",
       "    // Drag events report deltas in pixels, which we'd like to convert to\n",
       "    // millimeters.\n",
       "    root.data(\"px_per_mm\", px_per_mm);\n",
       "\n",
       "    root.selectAll(\"path\")\n",
       "        .forEach(function (element, i) {\n",
       "        sw = element.asPX(\"stroke-width\") * px_per_mm;\n",
       "        if (sw > 0) {\n",
       "            element.attribute(\"stroke-width\", sw);\n",
       "            element.attribute(\"vector-effect\", \"non-scaling-stroke\");\n",
       "        }\n",
       "    });\n",
       "\n",
       "    // Store ticks labels original tranformation\n",
       "    root.selectAll(\".xlabels > text, .ylabels > text\")\n",
       "        .forEach(function (element, i) {\n",
       "            var lm = element.transform().localMatrix;\n",
       "            element.data(\"static_transform\",\n",
       "                new Snap.Matrix(lm.a, lm.b, lm.c, lm.d, lm.e, lm.f));\n",
       "        });\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\");\n",
       "    var ygridlines = root.select(\".ygridlines\");\n",
       "    var xlabels = root.select(\".xlabels\");\n",
       "    var ylabels = root.select(\".ylabels\");\n",
       "\n",
       "    if (root.data(\"tx\") === undefined) root.data(\"tx\", 0);\n",
       "    if (root.data(\"ty\") === undefined) root.data(\"ty\", 0);\n",
       "    if (root.data(\"scale\") === undefined) root.data(\"scale\", 1.0);\n",
       "    if (root.data(\"xtickscales\") === undefined) {\n",
       "\n",
       "        // index all the tick scales that are listed\n",
       "        var xtickscales = {};\n",
       "        var ytickscales = {};\n",
       "        var add_x_tick_scales = function (element, i) {\n",
       "            xtickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "        var add_y_tick_scales = function (element, i) {\n",
       "            ytickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "\n",
       "        if (xgridlines) xgridlines.selectAll(\"path\").forEach(add_x_tick_scales);\n",
       "        if (ygridlines) ygridlines.selectAll(\"path\").forEach(add_y_tick_scales);\n",
       "        if (xlabels) xlabels.selectAll(\"text\").forEach(add_x_tick_scales);\n",
       "        if (ylabels) ylabels.selectAll(\"text\").forEach(add_y_tick_scales);\n",
       "\n",
       "        root.data(\"xtickscales\", xtickscales);\n",
       "        root.data(\"ytickscales\", ytickscales);\n",
       "        root.data(\"xtickscale\", 1.0);\n",
       "    }\n",
       "\n",
       "    var min_scale = 1.0, max_scale = 1.0;\n",
       "    for (scale in xtickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    for (scale in ytickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    root.data(\"min_scale\", min_scale);\n",
       "    root.data(\"max_scale\", max_scale);\n",
       "\n",
       "    // store the original positions of labels\n",
       "    if (xlabels) {\n",
       "        xlabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"x\", element.asPX(\"x\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    if (ylabels) {\n",
       "        ylabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"y\", element.asPX(\"y\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    // mark grid lines and ticks as in or out of scale.\n",
       "    var mark_inscale = function (element, i) {\n",
       "        element.attribute(\"gadfly:inscale\", element.attribute(\"gadfly:scale\") == 1.0);\n",
       "    };\n",
       "\n",
       "    if (xgridlines) xgridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (ygridlines) ygridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (xlabels) xlabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "    if (ylabels) ylabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "\n",
       "    // figure out the upper ond lower bounds on panning using the maximum\n",
       "    // and minum grid lines\n",
       "    var bounds = root.plotbounds();\n",
       "    var pan_bounds = {\n",
       "        x0: 0.0,\n",
       "        y0: 0.0,\n",
       "        x1: 0.0,\n",
       "        y1: 0.0\n",
       "    };\n",
       "\n",
       "    if (xgridlines) {\n",
       "        xgridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.x1 - bbox.x < pan_bounds.x0) {\n",
       "                        pan_bounds.x0 = bounds.x1 - bbox.x;\n",
       "                    }\n",
       "                    if (bounds.x0 - bbox.x > pan_bounds.x1) {\n",
       "                        pan_bounds.x1 = bounds.x0 - bbox.x;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (ygridlines) {\n",
       "        ygridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.y1 - bbox.y < pan_bounds.y0) {\n",
       "                        pan_bounds.y0 = bounds.y1 - bbox.y;\n",
       "                    }\n",
       "                    if (bounds.y0 - bbox.y > pan_bounds.y1) {\n",
       "                        pan_bounds.y1 = bounds.y0 - bbox.y;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // nudge these values a little\n",
       "    pan_bounds.x0 -= 5;\n",
       "    pan_bounds.x1 += 5;\n",
       "    pan_bounds.y0 -= 5;\n",
       "    pan_bounds.y1 += 5;\n",
       "    root.data(\"pan_bounds\", pan_bounds);\n",
       "\n",
       "    root.data(\"zoompan-ready\", true)\n",
       "};\n",
       "\n",
       "\n",
       "// drag actions, i.e. zooming and panning\n",
       "var pan_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        root.data(\"dx\", 0);\n",
       "        root.data(\"dy\", 0);\n",
       "        root.data(\"tx0\", root.data(\"tx\"));\n",
       "        root.data(\"ty0\", root.data(\"ty\"));\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        dx /= px_per_mm;\n",
       "        dy /= px_per_mm;\n",
       "\n",
       "        var tx0 = root.data(\"tx\"),\n",
       "            ty0 = root.data(\"ty\");\n",
       "\n",
       "        var dx0 = root.data(\"dx\"),\n",
       "            dy0 = root.data(\"dy\");\n",
       "\n",
       "        root.data(\"dx\", dx);\n",
       "        root.data(\"dy\", dy);\n",
       "\n",
       "        dx = dx - dx0;\n",
       "        dy = dy - dy0;\n",
       "\n",
       "        var tx = tx0 + dx,\n",
       "            ty = ty0 + dy;\n",
       "\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\"));\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        set_plot_pan_zoom(root, root.data(\"tx0\"), root.data(\"ty0\"), root.data(\"scale\"));\n",
       "    }\n",
       "};\n",
       "\n",
       "var zoom_box;\n",
       "var zoom_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        var bounds = root.plotbounds();\n",
       "        var width = bounds.x1 - bounds.x0,\n",
       "            height = bounds.y1 - bounds.y0;\n",
       "        var ratio = width / height;\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        x = xscalable ? x / px_per_mm : bounds.x0;\n",
       "        y = yscalable ? y / px_per_mm : bounds.y0;\n",
       "        var w = xscalable ? 0 : width;\n",
       "        var h = yscalable ? 0 : height;\n",
       "        zoom_box = root.rect(x, y, w, h).attr({\n",
       "            \"fill\": \"#000\",\n",
       "            \"opacity\": 0.25\n",
       "        });\n",
       "        zoom_box.data(\"ratio\", ratio);\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        var bounds = root.plotbounds();\n",
       "        if (yscalable) {\n",
       "            y /= px_per_mm;\n",
       "            y = Math.max(bounds.y0, y);\n",
       "            y = Math.min(bounds.y1, y);\n",
       "        } else {\n",
       "            y = bounds.y1;\n",
       "        }\n",
       "        if (xscalable) {\n",
       "            x /= px_per_mm;\n",
       "            x = Math.max(bounds.x0, x);\n",
       "            x = Math.min(bounds.x1, x);\n",
       "        } else {\n",
       "            x = bounds.x1;\n",
       "        }\n",
       "\n",
       "        dx = x - zoom_box.attr(\"x\");\n",
       "        dy = y - zoom_box.attr(\"y\");\n",
       "        if (xscalable && yscalable) {\n",
       "            var ratio = zoom_box.data(\"ratio\");\n",
       "            var width = Math.min(Math.abs(dx), ratio * Math.abs(dy));\n",
       "            var height = Math.min(Math.abs(dy), Math.abs(dx) / ratio);\n",
       "            dx = width * dx / Math.abs(dx);\n",
       "            dy = height * dy / Math.abs(dy);\n",
       "        }\n",
       "        var xoffset = 0,\n",
       "            yoffset = 0;\n",
       "        if (dx < 0) {\n",
       "            xoffset = dx;\n",
       "            dx = -1 * dx;\n",
       "        }\n",
       "        if (dy < 0) {\n",
       "            yoffset = dy;\n",
       "            dy = -1 * dy;\n",
       "        }\n",
       "        if (isNaN(dy)) {\n",
       "            dy = 0.0;\n",
       "        }\n",
       "        if (isNaN(dx)) {\n",
       "            dx = 0.0;\n",
       "        }\n",
       "        zoom_box.transform(\"T\" + xoffset + \",\" + yoffset);\n",
       "        zoom_box.attr(\"width\", dx);\n",
       "        zoom_box.attr(\"height\", dy);\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var zoom_bounds = zoom_box.getBBox();\n",
       "        if (zoom_bounds.width * zoom_bounds.height <= 0) {\n",
       "            return;\n",
       "        }\n",
       "        var plot_bounds = root.plotbounds();\n",
       "        var zoom_factor = 1.0;\n",
       "        if (yscalable) {\n",
       "            zoom_factor = (plot_bounds.y1 - plot_bounds.y0) / zoom_bounds.height;\n",
       "        } else {\n",
       "            zoom_factor = (plot_bounds.x1 - plot_bounds.x0) / zoom_bounds.width;\n",
       "        }\n",
       "        var tx = (root.data(\"tx\") - zoom_bounds.x) * zoom_factor + plot_bounds.x0,\n",
       "            ty = (root.data(\"ty\") - zoom_bounds.y) * zoom_factor + plot_bounds.y0;\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\") * zoom_factor);\n",
       "        zoom_box.remove();\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        zoom_box.remove();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onstart = function(x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var scalable = root.hasClass(\"xscalable\") || root.hasClass(\"yscalable\");\n",
       "    var zoomable = !event.altKey && !event.ctrlKey && event.shiftKey && scalable;\n",
       "    var panable = !event.altKey && !event.ctrlKey && !event.shiftKey && scalable;\n",
       "    var drag_action = zoomable ? zoom_action :\n",
       "                      panable  ? pan_action :\n",
       "                                 undefined;\n",
       "    root.data(\"drag_action\", drag_action);\n",
       "    if (drag_action) {\n",
       "        var cancel_drag_action = function(event) {\n",
       "            if (event.which == 27) { // esc key\n",
       "                drag_action.cancel(root);\n",
       "                root.data(\"drag_action\", undefined);\n",
       "            }\n",
       "        };\n",
       "        window.addEventListener(\"keyup\", cancel_drag_action);\n",
       "        root.data(\"cancel_drag_action\", cancel_drag_action);\n",
       "        drag_action.start(root, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.update(root, dx, dy, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onend = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    window.removeEventListener(\"keyup\", root.data(\"cancel_drag_action\"));\n",
       "    root.data(\"cancel_drag_action\", undefined);\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.end(root, event);\n",
       "    }\n",
       "    root.data(\"drag_action\", undefined);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_scroll = function(event) {\n",
       "    if (event.shiftKey) {\n",
       "        increase_zoom_by_position(this.plotroot(), 0.001 * event.wheelDelta);\n",
       "        event.preventDefault();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseover = function(event) {\n",
       "    this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseout = function(event) {\n",
       "     this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomout_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), -0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomin_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), 0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_track_click = function(event) {\n",
       "    // TODO\n",
       "};\n",
       "\n",
       "\n",
       "// Map slider position x to scale y using the function y = a*exp(b*x)+c.\n",
       "// The constants a, b, and c are solved using the constraint that the function\n",
       "// should go through the points (0; min_scale), (0.5; 1), and (1; max_scale).\n",
       "var scale_from_slider_position = function(position, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return a * Math.exp(b * position) + c;\n",
       "}\n",
       "\n",
       "// inverse of scale_from_slider_position\n",
       "var slider_position_from_scale = function(scale, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return 1 / b * Math.log((scale - c) / a);\n",
       "}\n",
       "\n",
       "var increase_zoom_by_position = function(root, delta_position, animate) {\n",
       "    var scale = root.data(\"scale\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\");\n",
       "    var position = slider_position_from_scale(scale, min_scale, max_scale);\n",
       "    position += delta_position;\n",
       "    scale = scale_from_slider_position(position, min_scale, max_scale);\n",
       "    set_zoom(root, scale, animate);\n",
       "}\n",
       "\n",
       "var set_zoom = function(root, scale, animate) {\n",
       "    var min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"scale\");\n",
       "    var new_scale = Math.max(min_scale, Math.min(scale, max_scale));\n",
       "    if (animate) {\n",
       "        Snap.animate(\n",
       "            old_scale,\n",
       "            new_scale,\n",
       "            function (new_scale) {\n",
       "                update_plot_scale(root, new_scale);\n",
       "            },\n",
       "            200);\n",
       "    } else {\n",
       "        update_plot_scale(root, new_scale);\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "var update_plot_scale = function(root, new_scale) {\n",
       "    var trans = scale_centered_translation(root, new_scale);\n",
       "    set_plot_pan_zoom(root, trans.x, trans.y, new_scale);\n",
       "\n",
       "    root.selectAll(\".zoomslider_thumb\")\n",
       "        .forEach(function (element, i) {\n",
       "            var min_pos = element.data(\"min_pos\"),\n",
       "                max_pos = element.data(\"max_pos\"),\n",
       "                min_scale = root.data(\"min_scale\"),\n",
       "                max_scale = root.data(\"max_scale\");\n",
       "            var xmid = (min_pos + max_pos) / 2;\n",
       "            var xpos = slider_position_from_scale(new_scale, min_scale, max_scale);\n",
       "            element.transform(new Snap.Matrix().translate(\n",
       "                Math.max(min_pos, Math.min(\n",
       "                         max_pos, min_pos + (max_pos - min_pos) * xpos)) - xmid, 0));\n",
       "    });\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var min_pos = this.data(\"min_pos\"),\n",
       "        max_pos = this.data(\"max_pos\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"old_scale\");\n",
       "\n",
       "    var px_per_mm = root.data(\"px_per_mm\");\n",
       "    dx /= px_per_mm;\n",
       "    dy /= px_per_mm;\n",
       "\n",
       "    var xmid = (min_pos + max_pos) / 2;\n",
       "    var xpos = slider_position_from_scale(old_scale, min_scale, max_scale) +\n",
       "                   dx / (max_pos - min_pos);\n",
       "\n",
       "    // compute the new scale\n",
       "    var new_scale = scale_from_slider_position(xpos, min_scale, max_scale);\n",
       "    new_scale = Math.min(max_scale, Math.max(min_scale, new_scale));\n",
       "\n",
       "    update_plot_scale(root, new_scale);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragstart = function(x, y, event) {\n",
       "    this.animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    // keep track of what the scale was when we started dragging\n",
       "    root.data(\"old_scale\", root.data(\"scale\"));\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragend = function(event) {\n",
       "    this.animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "var toggle_color_class = function(root, color_class, ison) {\n",
       "    var guides = root.selectAll(\".guide.\" + color_class + \",.guide .\" + color_class);\n",
       "    var geoms = root.selectAll(\".geometry.\" + color_class + \",.geometry .\" + color_class);\n",
       "    if (ison) {\n",
       "        guides.animate({opacity: 0.5}, 250);\n",
       "        geoms.animate({opacity: 0.0}, 250);\n",
       "    } else {\n",
       "        guides.animate({opacity: 1.0}, 250);\n",
       "        geoms.animate({opacity: 1.0}, 250);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.colorkey_swatch_click = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    var color_class = this.data(\"color_class\");\n",
       "\n",
       "    if (event.shiftKey) {\n",
       "        root.selectAll(\".colorkey text\")\n",
       "            .forEach(function (element) {\n",
       "                var other_color_class = element.data(\"color_class\");\n",
       "                if (other_color_class != color_class) {\n",
       "                    toggle_color_class(root, other_color_class,\n",
       "                                       element.attr(\"opacity\") == 1.0);\n",
       "                }\n",
       "            });\n",
       "    } else {\n",
       "        toggle_color_class(root, color_class, this.attr(\"opacity\") == 1.0);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "return Gadfly;\n",
       "\n",
       "}));\n",
       "\n",
       "\n",
       "//@ sourceURL=gadfly.js\n",
       "\n",
       "(function (glob, factory) {\n",
       "    // AMD support\n",
       "      if (typeof require === \"function\" && typeof define === \"function\" && define.amd) {\n",
       "        require([\"Snap.svg\", \"Gadfly\"], function (Snap, Gadfly) {\n",
       "            factory(Snap, Gadfly);\n",
       "        });\n",
       "      } else {\n",
       "          factory(glob.Snap, glob.Gadfly);\n",
       "      }\n",
       "})(window, function (Snap, Gadfly) {\n",
       "    var fig = Snap(\"#img-49eebe7e\");\n",
       "fig.select(\"#img-49eebe7e-5\")\n",
       "   .init_gadfly();\n",
       "fig.select(\"#img-49eebe7e-7\")\n",
       "   .plotroot().data(\"unfocused_ygrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-49eebe7e-7\")\n",
       "   .plotroot().data(\"focused_ygrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-49eebe7e-8\")\n",
       "   .plotroot().data(\"unfocused_xgrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-49eebe7e-8\")\n",
       "   .plotroot().data(\"focused_xgrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-49eebe7e-37\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-49eebe7e-37\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-49eebe7e-37\")\n",
       "   .click(Gadfly.zoomslider_zoomin_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "fig.select(\"#img-49eebe7e-39\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-49eebe7e-39\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-49eebe7e-39\")\n",
       "   .click(Gadfly.zoomslider_track_click);\n",
       "fig.select(\"#img-49eebe7e-40\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-49eebe7e-40\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-49eebe7e-40\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-49eebe7e-40\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-49eebe7e-40\")\n",
       "   .drag(Gadfly.zoomslider_thumb_dragmove,\n",
       "     Gadfly.zoomslider_thumb_dragstart,\n",
       "     Gadfly.zoomslider_thumb_dragend)\n",
       ";\n",
       "fig.select(\"#img-49eebe7e-41\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-49eebe7e-41\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-49eebe7e-41\")\n",
       "   .click(Gadfly.zoomslider_zoomout_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "    });\n",
       "]]> </script>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "Plot(...)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m = mean(chn1[:m])\n",
    "l_simple_g_mean = layer(xintercept=[m], Geom.vline)\n",
    "l_simple_g = layer([x->pdf(Normal(m, 1), x)], -15, 15, Geom.line)\n",
    "plot(l_x, l_simple_g_mean, l_simple_g)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A better model\n",
    "\n",
    "$$ \\sigma^2 \\sim \\textit{Inv-Gamma}(2, 3),  \\mu \\sim \\textit{Normal}(0, \\sigma) $$\n",
    "$$ x_i \\sim \\textit{Normal}(\\mu, \\sigma), i = 1 \\dots N  $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "g_better (generic function with 2 methods)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "@model g_better(x) = begin\n",
    "    s ~ InverseGamma(2, 3)\n",
    "    m ~ Normal(0, sqrt(s))\n",
    "    for i = 1:length(x)\n",
    "        x[i] ~ Normal(m, sqrt(s))\n",
    "    end\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "[Turing]:  Assume - `s` is a parameter\n",
      "  in @~(::Any, ::Any) at compiler.jl:56\n",
      "\r",
      "[Turing]:  Assume - `m` is a parameter (ignoring `m` found in global scope)\n",
      "  in @~(::Any, ::Any) at compiler.jl:56\n",
      "\r",
      "[Turing]:  Observe - `x` is an observation\n",
      "  in @~(::Any, ::Any) at compiler.jl:35\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "[HMC] Sampling... 36%  ETA: 0:00:02\r",
      "[HMC] Sampling... 86%  ETA: 0:00:00"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[HMC] Finished with\n",
      "  Running time        = 2.222356753000002;\n",
      "  Accept rate         = 0.979;\n",
      "  #lf / sample        = 3.996;\n",
      "  #evals / sample     = 3.998;\n",
      "  pre-cond. diag mat  = [1.0,1.0].\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "[HMC] Sampling...100% Time: 0:00:02\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Object of type \"Turing.Chain\"\n",
       "\n",
       "Iterations = 1:1000\n",
       "Thinning interval = 1\n",
       "Chains = 1\n",
       "Samples per chain = 1000\n",
       "\n",
       "[0.445958 -99.5293 … 0.0127689 1.68708; 1.44344 -61.9003 … 0.197052 1316.47; … ; 2.158 -38.8808 … 0.00243614 26.6179; 3.32304 -40.3803 … 0.00267126 20.9118]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chn2 = sample(g_better(x), HMC(1000, 0.2, 4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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       "f:e,unbind:b(this.node||document,d,e,f||this)}));return this};a[\"un\"+d]=A[\"un\"+d]=function(a){for(var b=this.events||[],e=b.length;e--;)if(b[e].name==d&&(b[e].f==a||!a)){b[e].unbind();b.splice(e,1);!b.length&&delete this.events;break}return this}})(v[y]);A.hover=function(a,b,d,e){return this.mouseover(a,d).mouseout(b,e||d)};A.unhover=function(a,b){return this.unmouseover(a).unmouseout(b)};var r=[];A.drag=function(b,d,f,h,n,p){function u(r,v,w){(r.originalEvent||r).preventDefault();this._drag.x=v;\n",
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       "A.undrag=function(){for(var b=r.length;b--;)r[b].el==this&&(this.unmousedown(r[b].start),r.splice(b,1),k.unbind(\"snap.drag.*.\"+this.id));!r.length&&a.unmousemove(e).unmouseup(l);return this}});C.plugin(function(a,v,y,C){y=y.prototype;var A=/^\\s*url\\((.+)\\)/,w=String,z=a._.$;a.filter={};y.filter=function(d){var f=this;\"svg\"!=f.type&&(f=f.paper);d=a.parse(w(d));var k=a._.id(),u=z(\"filter\");z(u,{id:k,filterUnits:\"userSpaceOnUse\"});u.appendChild(d.node);f.defs.appendChild(u);return new v(u)};k.on(\"snap.util.getattr.filter\",\n",
       "function(){k.stop();var d=z(this.node,\"filter\");if(d)return(d=w(d).match(A))&&a.select(d[1])});k.on(\"snap.util.attr.filter\",function(d){if(d instanceof v&&\"filter\"==d.type){k.stop();var f=d.node.id;f||(z(d.node,{id:d.id}),f=d.id);z(this.node,{filter:a.url(f)})}d&&\"none\"!=d||(k.stop(),this.node.removeAttribute(\"filter\"))});a.filter.blur=function(d,f){null==d&&(d=2);return a.format('<feGaussianBlur stdDeviation=\"{def}\"/>',{def:null==f?d:[d,f]})};a.filter.blur.toString=function(){return this()};a.filter.shadow=\n",
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       "amount2:1-d})};a.filter.invert.toString=function(){return this()};a.filter.brightness=function(d){null==d&&(d=1);return a.format('<feComponentTransfer><feFuncR type=\"linear\" slope=\"{amount}\"/><feFuncG type=\"linear\" slope=\"{amount}\"/><feFuncB type=\"linear\" slope=\"{amount}\"/></feComponentTransfer>',{amount:d})};a.filter.brightness.toString=function(){return this()};a.filter.contrast=function(d){null==d&&(d=1);return a.format('<feComponentTransfer><feFuncR type=\"linear\" slope=\"{amount}\" intercept=\"{amount2}\"/><feFuncG type=\"linear\" slope=\"{amount}\" intercept=\"{amount2}\"/><feFuncB type=\"linear\" slope=\"{amount}\" intercept=\"{amount2}\"/></feComponentTransfer>',\n",
       "{amount:d,amount2:0.5-d/2})};a.filter.contrast.toString=function(){return this()}});return C});\n",
       "\n",
       "]]> </script>\n",
       "<script> <![CDATA[\n",
       "\n",
       "(function (glob, factory) {\n",
       "    // AMD support\n",
       "    if (typeof define === \"function\" && define.amd) {\n",
       "        // Define as an anonymous module\n",
       "        define(\"Gadfly\", [\"Snap.svg\"], function (Snap) {\n",
       "            return factory(Snap);\n",
       "        });\n",
       "    } else {\n",
       "        // Browser globals (glob is window)\n",
       "        // Snap adds itself to window\n",
       "        glob.Gadfly = factory(glob.Snap);\n",
       "    }\n",
       "}(this, function (Snap) {\n",
       "\n",
       "var Gadfly = {};\n",
       "\n",
       "// Get an x/y coordinate value in pixels\n",
       "var xPX = function(fig, x) {\n",
       "    var client_box = fig.node.getBoundingClientRect();\n",
       "    return x * fig.node.viewBox.baseVal.width / client_box.width;\n",
       "};\n",
       "\n",
       "var yPX = function(fig, y) {\n",
       "    var client_box = fig.node.getBoundingClientRect();\n",
       "    return y * fig.node.viewBox.baseVal.height / client_box.height;\n",
       "};\n",
       "\n",
       "\n",
       "Snap.plugin(function (Snap, Element, Paper, global) {\n",
       "    // Traverse upwards from a snap element to find and return the first\n",
       "    // note with the \"plotroot\" class.\n",
       "    Element.prototype.plotroot = function () {\n",
       "        var element = this;\n",
       "        while (!element.hasClass(\"plotroot\") && element.parent() != null) {\n",
       "            element = element.parent();\n",
       "        }\n",
       "        return element;\n",
       "    };\n",
       "\n",
       "    Element.prototype.svgroot = function () {\n",
       "        var element = this;\n",
       "        while (element.node.nodeName != \"svg\" && element.parent() != null) {\n",
       "            element = element.parent();\n",
       "        }\n",
       "        return element;\n",
       "    };\n",
       "\n",
       "    Element.prototype.plotbounds = function () {\n",
       "        var root = this.plotroot()\n",
       "        var bbox = root.select(\".guide.background\").node.getBBox();\n",
       "        return {\n",
       "            x0: bbox.x,\n",
       "            x1: bbox.x + bbox.width,\n",
       "            y0: bbox.y,\n",
       "            y1: bbox.y + bbox.height\n",
       "        };\n",
       "    };\n",
       "\n",
       "    Element.prototype.plotcenter = function () {\n",
       "        var root = this.plotroot()\n",
       "        var bbox = root.select(\".guide.background\").node.getBBox();\n",
       "        return {\n",
       "            x: bbox.x + bbox.width / 2,\n",
       "            y: bbox.y + bbox.height / 2\n",
       "        };\n",
       "    };\n",
       "\n",
       "    // Emulate IE style mouseenter/mouseleave events, since Microsoft always\n",
       "    // does everything right.\n",
       "    // See: http://www.dynamic-tools.net/toolbox/isMouseLeaveOrEnter/\n",
       "    var events = [\"mouseenter\", \"mouseleave\"];\n",
       "\n",
       "    for (i in events) {\n",
       "        (function (event_name) {\n",
       "            var event_name = events[i];\n",
       "            Element.prototype[event_name] = function (fn, scope) {\n",
       "                if (Snap.is(fn, \"function\")) {\n",
       "                    var fn2 = function (event) {\n",
       "                        if (event.type != \"mouseover\" && event.type != \"mouseout\") {\n",
       "                            return;\n",
       "                        }\n",
       "\n",
       "                        var reltg = event.relatedTarget ? event.relatedTarget :\n",
       "                            event.type == \"mouseout\" ? event.toElement : event.fromElement;\n",
       "                        while (reltg && reltg != this.node) reltg = reltg.parentNode;\n",
       "\n",
       "                        if (reltg != this.node) {\n",
       "                            return fn.apply(this, event);\n",
       "                        }\n",
       "                    };\n",
       "\n",
       "                    if (event_name == \"mouseenter\") {\n",
       "                        this.mouseover(fn2, scope);\n",
       "                    } else {\n",
       "                        this.mouseout(fn2, scope);\n",
       "                    }\n",
       "                }\n",
       "                return this;\n",
       "            };\n",
       "        })(events[i]);\n",
       "    }\n",
       "\n",
       "\n",
       "    Element.prototype.mousewheel = function (fn, scope) {\n",
       "        if (Snap.is(fn, \"function\")) {\n",
       "            var el = this;\n",
       "            var fn2 = function (event) {\n",
       "                fn.apply(el, [event]);\n",
       "            };\n",
       "        }\n",
       "\n",
       "        this.node.addEventListener(\n",
       "            /Firefox/i.test(navigator.userAgent) ? \"DOMMouseScroll\" : \"mousewheel\",\n",
       "            fn2);\n",
       "\n",
       "        return this;\n",
       "    };\n",
       "\n",
       "\n",
       "    // Snap's attr function can be too slow for things like panning/zooming.\n",
       "    // This is a function to directly update element attributes without going\n",
       "    // through eve.\n",
       "    Element.prototype.attribute = function(key, val) {\n",
       "        if (val === undefined) {\n",
       "            return this.node.getAttribute(key);\n",
       "        } else {\n",
       "            this.node.setAttribute(key, val);\n",
       "            return this;\n",
       "        }\n",
       "    };\n",
       "\n",
       "    Element.prototype.init_gadfly = function() {\n",
       "        this.mouseenter(Gadfly.plot_mouseover)\n",
       "            .mouseleave(Gadfly.plot_mouseout)\n",
       "            .dblclick(Gadfly.plot_dblclick)\n",
       "            .mousewheel(Gadfly.guide_background_scroll)\n",
       "            .drag(Gadfly.guide_background_drag_onmove,\n",
       "                  Gadfly.guide_background_drag_onstart,\n",
       "                  Gadfly.guide_background_drag_onend);\n",
       "        this.mouseenter(function (event) {\n",
       "            init_pan_zoom(this.plotroot());\n",
       "        });\n",
       "        return this;\n",
       "    };\n",
       "});\n",
       "\n",
       "\n",
       "// When the plot is moused over, emphasize the grid lines.\n",
       "Gadfly.plot_mouseover = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    var keyboard_zoom = function(event) {\n",
       "        if (event.which == 187) { // plus\n",
       "            increase_zoom_by_position(root, 0.1, true);\n",
       "        } else if (event.which == 189) { // minus\n",
       "            increase_zoom_by_position(root, -0.1, true);\n",
       "        }\n",
       "    };\n",
       "    root.data(\"keyboard_zoom\", keyboard_zoom);\n",
       "    window.addEventListener(\"keyup\", keyboard_zoom);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    xgridlines.data(\"unfocused_strokedash\",\n",
       "                    xgridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "    ygridlines.data(\"unfocused_strokedash\",\n",
       "                    ygridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "\n",
       "    // emphasize grid lines\n",
       "    var destcolor = root.data(\"focused_xgrid_color\");\n",
       "    xgridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"focused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // reveal zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 1.0}, 250);\n",
       "};\n",
       "\n",
       "// Reset pan and zoom on double click\n",
       "Gadfly.plot_dblclick = function(event) {\n",
       "  set_plot_pan_zoom(this.plotroot(), 0.0, 0.0, 1.0);\n",
       "};\n",
       "\n",
       "// Unemphasize grid lines on mouse out.\n",
       "Gadfly.plot_mouseout = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    window.removeEventListener(\"keyup\", root.data(\"keyboard_zoom\"));\n",
       "    root.data(\"keyboard_zoom\", undefined);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    var destcolor = root.data(\"unfocused_xgrid_color\");\n",
       "\n",
       "    xgridlines.attribute(\"stroke-dasharray\", xgridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"unfocused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", ygridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // hide zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 0.0}, 250);\n",
       "};\n",
       "\n",
       "\n",
       "var set_geometry_transform = function(root, tx, ty, scale) {\n",
       "    var xscalable = root.hasClass(\"xscalable\"),\n",
       "        yscalable = root.hasClass(\"yscalable\");\n",
       "\n",
       "    var old_scale = root.data(\"scale\");\n",
       "\n",
       "    var xscale = xscalable ? scale : 1.0,\n",
       "        yscale = yscalable ? scale : 1.0;\n",
       "\n",
       "    tx = xscalable ? tx : 0.0;\n",
       "    ty = yscalable ? ty : 0.0;\n",
       "\n",
       "    var t = new Snap.Matrix().translate(tx, ty).scale(xscale, yscale);\n",
       "\n",
       "    root.selectAll(\".geometry, image\")\n",
       "        .forEach(function (element, i) {\n",
       "            element.transform(t);\n",
       "        });\n",
       "\n",
       "    bounds = root.plotbounds();\n",
       "\n",
       "    if (yscalable) {\n",
       "        var xfixed_t = new Snap.Matrix().translate(0, ty).scale(1.0, yscale);\n",
       "        root.selectAll(\".xfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(xfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".ylabels\")\n",
       "            .transform(xfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1, 1/scale, cx, cy).add(st);\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var y = cy * scale + ty;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.y0 <= y && y <= bounds.y1 ? \"visible\" : \"hidden\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (xscalable) {\n",
       "        var yfixed_t = new Snap.Matrix().translate(tx, 0).scale(xscale, 1.0);\n",
       "        var xtrans = new Snap.Matrix().translate(tx, 0);\n",
       "        root.selectAll(\".yfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(yfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".xlabels\")\n",
       "            .transform(yfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1/scale, 1, cx, cy).add(st);\n",
       "\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var x = cx * scale + tx;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.x0 <= x && x <= bounds.x1 ? \"visible\" : \"hidden\");\n",
       "                    }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // we must unscale anything that is scale invariance: widths, raiduses, etc.\n",
       "    var size_attribs = [\"font-size\"];\n",
       "    var unscaled_selection = \".geometry, .geometry *\";\n",
       "    if (xscalable) {\n",
       "        size_attribs.push(\"rx\");\n",
       "        unscaled_selection += \", .xgridlines\";\n",
       "    }\n",
       "    if (yscalable) {\n",
       "        size_attribs.push(\"ry\");\n",
       "        unscaled_selection += \", .ygridlines\";\n",
       "    }\n",
       "\n",
       "    root.selectAll(unscaled_selection)\n",
       "        .forEach(function (element, i) {\n",
       "            // circle need special help\n",
       "            if (element.node.nodeName == \"circle\") {\n",
       "                var cx = element.attribute(\"cx\"),\n",
       "                    cy = element.attribute(\"cy\");\n",
       "                unscale_t = new Snap.Matrix().scale(1/xscale, 1/yscale,\n",
       "                                                        cx, cy);\n",
       "                element.transform(unscale_t);\n",
       "                return;\n",
       "            }\n",
       "\n",
       "            for (i in size_attribs) {\n",
       "                var key = size_attribs[i];\n",
       "                var val = parseFloat(element.attribute(key));\n",
       "                if (val !== undefined && val != 0 && !isNaN(val)) {\n",
       "                    element.attribute(key, val * old_scale / scale);\n",
       "                }\n",
       "            }\n",
       "        });\n",
       "};\n",
       "\n",
       "\n",
       "// Find the most appropriate tick scale and update label visibility.\n",
       "var update_tickscale = function(root, scale, axis) {\n",
       "    if (!root.hasClass(axis + \"scalable\")) return;\n",
       "\n",
       "    var tickscales = root.data(axis + \"tickscales\");\n",
       "    var best_tickscale = 1.0;\n",
       "    var best_tickscale_dist = Infinity;\n",
       "    for (tickscale in tickscales) {\n",
       "        var dist = Math.abs(Math.log(tickscale) - Math.log(scale));\n",
       "        if (dist < best_tickscale_dist) {\n",
       "            best_tickscale_dist = dist;\n",
       "            best_tickscale = tickscale;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    if (best_tickscale != root.data(axis + \"tickscale\")) {\n",
       "        root.data(axis + \"tickscale\", best_tickscale);\n",
       "        var mark_inscale_gridlines = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        var mark_inscale_labels = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        root.select(\".\" + axis + \"gridlines\").selectAll(\"path\").forEach(mark_inscale_gridlines);\n",
       "        root.select(\".\" + axis + \"labels\").selectAll(\"text\").forEach(mark_inscale_labels);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "var set_plot_pan_zoom = function(root, tx, ty, scale) {\n",
       "    var old_scale = root.data(\"scale\");\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    // compute the viewport derived from tx, ty, and scale\n",
       "    var x_min = -width * scale - (scale * width - width),\n",
       "        x_max = width * scale,\n",
       "        y_min = -height * scale - (scale * height - height),\n",
       "        y_max = height * scale;\n",
       "\n",
       "    var x0 = bounds.x0 - scale * bounds.x0,\n",
       "        y0 = bounds.y0 - scale * bounds.y0;\n",
       "\n",
       "    var tx = Math.max(Math.min(tx - x0, x_max), x_min),\n",
       "        ty = Math.max(Math.min(ty - y0, y_max), y_min);\n",
       "\n",
       "    tx += x0;\n",
       "    ty += y0;\n",
       "\n",
       "    // when the scale change, we may need to alter which set of\n",
       "    // ticks is being displayed\n",
       "    if (scale != old_scale) {\n",
       "        update_tickscale(root, scale, \"x\");\n",
       "        update_tickscale(root, scale, \"y\");\n",
       "    }\n",
       "\n",
       "    set_geometry_transform(root, tx, ty, scale);\n",
       "\n",
       "    root.data(\"scale\", scale);\n",
       "    root.data(\"tx\", tx);\n",
       "    root.data(\"ty\", ty);\n",
       "};\n",
       "\n",
       "\n",
       "var scale_centered_translation = function(root, scale) {\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    var tx0 = root.data(\"tx\"),\n",
       "        ty0 = root.data(\"ty\");\n",
       "\n",
       "    var scale0 = root.data(\"scale\");\n",
       "\n",
       "    // how off from center the current view is\n",
       "    var xoff = tx0 - (bounds.x0 * (1 - scale0) + (width * (1 - scale0)) / 2),\n",
       "        yoff = ty0 - (bounds.y0 * (1 - scale0) + (height * (1 - scale0)) / 2);\n",
       "\n",
       "    // rescale offsets\n",
       "    xoff = xoff * scale / scale0;\n",
       "    yoff = yoff * scale / scale0;\n",
       "\n",
       "    // adjust for the panel position being scaled\n",
       "    var x_edge_adjust = bounds.x0 * (1 - scale),\n",
       "        y_edge_adjust = bounds.y0 * (1 - scale);\n",
       "\n",
       "    return {\n",
       "        x: xoff + x_edge_adjust + (width - width * scale) / 2,\n",
       "        y: yoff + y_edge_adjust + (height - height * scale) / 2\n",
       "    };\n",
       "};\n",
       "\n",
       "\n",
       "// Initialize data for panning zooming if it isn't already.\n",
       "var init_pan_zoom = function(root) {\n",
       "    if (root.data(\"zoompan-ready\")) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    // The non-scaling-stroke trick. Rather than try to correct for the\n",
       "    // stroke-width when zooming, we force it to a fixed value.\n",
       "    var px_per_mm = root.node.getCTM().a;\n",
       "\n",
       "    // Drag events report deltas in pixels, which we'd like to convert to\n",
       "    // millimeters.\n",
       "    root.data(\"px_per_mm\", px_per_mm);\n",
       "\n",
       "    root.selectAll(\"path\")\n",
       "        .forEach(function (element, i) {\n",
       "        sw = element.asPX(\"stroke-width\") * px_per_mm;\n",
       "        if (sw > 0) {\n",
       "            element.attribute(\"stroke-width\", sw);\n",
       "            element.attribute(\"vector-effect\", \"non-scaling-stroke\");\n",
       "        }\n",
       "    });\n",
       "\n",
       "    // Store ticks labels original tranformation\n",
       "    root.selectAll(\".xlabels > text, .ylabels > text\")\n",
       "        .forEach(function (element, i) {\n",
       "            var lm = element.transform().localMatrix;\n",
       "            element.data(\"static_transform\",\n",
       "                new Snap.Matrix(lm.a, lm.b, lm.c, lm.d, lm.e, lm.f));\n",
       "        });\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\");\n",
       "    var ygridlines = root.select(\".ygridlines\");\n",
       "    var xlabels = root.select(\".xlabels\");\n",
       "    var ylabels = root.select(\".ylabels\");\n",
       "\n",
       "    if (root.data(\"tx\") === undefined) root.data(\"tx\", 0);\n",
       "    if (root.data(\"ty\") === undefined) root.data(\"ty\", 0);\n",
       "    if (root.data(\"scale\") === undefined) root.data(\"scale\", 1.0);\n",
       "    if (root.data(\"xtickscales\") === undefined) {\n",
       "\n",
       "        // index all the tick scales that are listed\n",
       "        var xtickscales = {};\n",
       "        var ytickscales = {};\n",
       "        var add_x_tick_scales = function (element, i) {\n",
       "            xtickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "        var add_y_tick_scales = function (element, i) {\n",
       "            ytickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "\n",
       "        if (xgridlines) xgridlines.selectAll(\"path\").forEach(add_x_tick_scales);\n",
       "        if (ygridlines) ygridlines.selectAll(\"path\").forEach(add_y_tick_scales);\n",
       "        if (xlabels) xlabels.selectAll(\"text\").forEach(add_x_tick_scales);\n",
       "        if (ylabels) ylabels.selectAll(\"text\").forEach(add_y_tick_scales);\n",
       "\n",
       "        root.data(\"xtickscales\", xtickscales);\n",
       "        root.data(\"ytickscales\", ytickscales);\n",
       "        root.data(\"xtickscale\", 1.0);\n",
       "    }\n",
       "\n",
       "    var min_scale = 1.0, max_scale = 1.0;\n",
       "    for (scale in xtickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    for (scale in ytickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    root.data(\"min_scale\", min_scale);\n",
       "    root.data(\"max_scale\", max_scale);\n",
       "\n",
       "    // store the original positions of labels\n",
       "    if (xlabels) {\n",
       "        xlabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"x\", element.asPX(\"x\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    if (ylabels) {\n",
       "        ylabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"y\", element.asPX(\"y\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    // mark grid lines and ticks as in or out of scale.\n",
       "    var mark_inscale = function (element, i) {\n",
       "        element.attribute(\"gadfly:inscale\", element.attribute(\"gadfly:scale\") == 1.0);\n",
       "    };\n",
       "\n",
       "    if (xgridlines) xgridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (ygridlines) ygridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (xlabels) xlabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "    if (ylabels) ylabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "\n",
       "    // figure out the upper ond lower bounds on panning using the maximum\n",
       "    // and minum grid lines\n",
       "    var bounds = root.plotbounds();\n",
       "    var pan_bounds = {\n",
       "        x0: 0.0,\n",
       "        y0: 0.0,\n",
       "        x1: 0.0,\n",
       "        y1: 0.0\n",
       "    };\n",
       "\n",
       "    if (xgridlines) {\n",
       "        xgridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.x1 - bbox.x < pan_bounds.x0) {\n",
       "                        pan_bounds.x0 = bounds.x1 - bbox.x;\n",
       "                    }\n",
       "                    if (bounds.x0 - bbox.x > pan_bounds.x1) {\n",
       "                        pan_bounds.x1 = bounds.x0 - bbox.x;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (ygridlines) {\n",
       "        ygridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.y1 - bbox.y < pan_bounds.y0) {\n",
       "                        pan_bounds.y0 = bounds.y1 - bbox.y;\n",
       "                    }\n",
       "                    if (bounds.y0 - bbox.y > pan_bounds.y1) {\n",
       "                        pan_bounds.y1 = bounds.y0 - bbox.y;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // nudge these values a little\n",
       "    pan_bounds.x0 -= 5;\n",
       "    pan_bounds.x1 += 5;\n",
       "    pan_bounds.y0 -= 5;\n",
       "    pan_bounds.y1 += 5;\n",
       "    root.data(\"pan_bounds\", pan_bounds);\n",
       "\n",
       "    root.data(\"zoompan-ready\", true)\n",
       "};\n",
       "\n",
       "\n",
       "// drag actions, i.e. zooming and panning\n",
       "var pan_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        root.data(\"dx\", 0);\n",
       "        root.data(\"dy\", 0);\n",
       "        root.data(\"tx0\", root.data(\"tx\"));\n",
       "        root.data(\"ty0\", root.data(\"ty\"));\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        dx /= px_per_mm;\n",
       "        dy /= px_per_mm;\n",
       "\n",
       "        var tx0 = root.data(\"tx\"),\n",
       "            ty0 = root.data(\"ty\");\n",
       "\n",
       "        var dx0 = root.data(\"dx\"),\n",
       "            dy0 = root.data(\"dy\");\n",
       "\n",
       "        root.data(\"dx\", dx);\n",
       "        root.data(\"dy\", dy);\n",
       "\n",
       "        dx = dx - dx0;\n",
       "        dy = dy - dy0;\n",
       "\n",
       "        var tx = tx0 + dx,\n",
       "            ty = ty0 + dy;\n",
       "\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\"));\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        set_plot_pan_zoom(root, root.data(\"tx0\"), root.data(\"ty0\"), root.data(\"scale\"));\n",
       "    }\n",
       "};\n",
       "\n",
       "var zoom_box;\n",
       "var zoom_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        var bounds = root.plotbounds();\n",
       "        var width = bounds.x1 - bounds.x0,\n",
       "            height = bounds.y1 - bounds.y0;\n",
       "        var ratio = width / height;\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        x = xscalable ? x / px_per_mm : bounds.x0;\n",
       "        y = yscalable ? y / px_per_mm : bounds.y0;\n",
       "        var w = xscalable ? 0 : width;\n",
       "        var h = yscalable ? 0 : height;\n",
       "        zoom_box = root.rect(x, y, w, h).attr({\n",
       "            \"fill\": \"#000\",\n",
       "            \"opacity\": 0.25\n",
       "        });\n",
       "        zoom_box.data(\"ratio\", ratio);\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        var bounds = root.plotbounds();\n",
       "        if (yscalable) {\n",
       "            y /= px_per_mm;\n",
       "            y = Math.max(bounds.y0, y);\n",
       "            y = Math.min(bounds.y1, y);\n",
       "        } else {\n",
       "            y = bounds.y1;\n",
       "        }\n",
       "        if (xscalable) {\n",
       "            x /= px_per_mm;\n",
       "            x = Math.max(bounds.x0, x);\n",
       "            x = Math.min(bounds.x1, x);\n",
       "        } else {\n",
       "            x = bounds.x1;\n",
       "        }\n",
       "\n",
       "        dx = x - zoom_box.attr(\"x\");\n",
       "        dy = y - zoom_box.attr(\"y\");\n",
       "        if (xscalable && yscalable) {\n",
       "            var ratio = zoom_box.data(\"ratio\");\n",
       "            var width = Math.min(Math.abs(dx), ratio * Math.abs(dy));\n",
       "            var height = Math.min(Math.abs(dy), Math.abs(dx) / ratio);\n",
       "            dx = width * dx / Math.abs(dx);\n",
       "            dy = height * dy / Math.abs(dy);\n",
       "        }\n",
       "        var xoffset = 0,\n",
       "            yoffset = 0;\n",
       "        if (dx < 0) {\n",
       "            xoffset = dx;\n",
       "            dx = -1 * dx;\n",
       "        }\n",
       "        if (dy < 0) {\n",
       "            yoffset = dy;\n",
       "            dy = -1 * dy;\n",
       "        }\n",
       "        if (isNaN(dy)) {\n",
       "            dy = 0.0;\n",
       "        }\n",
       "        if (isNaN(dx)) {\n",
       "            dx = 0.0;\n",
       "        }\n",
       "        zoom_box.transform(\"T\" + xoffset + \",\" + yoffset);\n",
       "        zoom_box.attr(\"width\", dx);\n",
       "        zoom_box.attr(\"height\", dy);\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var zoom_bounds = zoom_box.getBBox();\n",
       "        if (zoom_bounds.width * zoom_bounds.height <= 0) {\n",
       "            return;\n",
       "        }\n",
       "        var plot_bounds = root.plotbounds();\n",
       "        var zoom_factor = 1.0;\n",
       "        if (yscalable) {\n",
       "            zoom_factor = (plot_bounds.y1 - plot_bounds.y0) / zoom_bounds.height;\n",
       "        } else {\n",
       "            zoom_factor = (plot_bounds.x1 - plot_bounds.x0) / zoom_bounds.width;\n",
       "        }\n",
       "        var tx = (root.data(\"tx\") - zoom_bounds.x) * zoom_factor + plot_bounds.x0,\n",
       "            ty = (root.data(\"ty\") - zoom_bounds.y) * zoom_factor + plot_bounds.y0;\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\") * zoom_factor);\n",
       "        zoom_box.remove();\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        zoom_box.remove();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onstart = function(x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var scalable = root.hasClass(\"xscalable\") || root.hasClass(\"yscalable\");\n",
       "    var zoomable = !event.altKey && !event.ctrlKey && event.shiftKey && scalable;\n",
       "    var panable = !event.altKey && !event.ctrlKey && !event.shiftKey && scalable;\n",
       "    var drag_action = zoomable ? zoom_action :\n",
       "                      panable  ? pan_action :\n",
       "                                 undefined;\n",
       "    root.data(\"drag_action\", drag_action);\n",
       "    if (drag_action) {\n",
       "        var cancel_drag_action = function(event) {\n",
       "            if (event.which == 27) { // esc key\n",
       "                drag_action.cancel(root);\n",
       "                root.data(\"drag_action\", undefined);\n",
       "            }\n",
       "        };\n",
       "        window.addEventListener(\"keyup\", cancel_drag_action);\n",
       "        root.data(\"cancel_drag_action\", cancel_drag_action);\n",
       "        drag_action.start(root, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.update(root, dx, dy, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onend = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    window.removeEventListener(\"keyup\", root.data(\"cancel_drag_action\"));\n",
       "    root.data(\"cancel_drag_action\", undefined);\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.end(root, event);\n",
       "    }\n",
       "    root.data(\"drag_action\", undefined);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_scroll = function(event) {\n",
       "    if (event.shiftKey) {\n",
       "        increase_zoom_by_position(this.plotroot(), 0.001 * event.wheelDelta);\n",
       "        event.preventDefault();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseover = function(event) {\n",
       "    this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseout = function(event) {\n",
       "     this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomout_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), -0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomin_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), 0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_track_click = function(event) {\n",
       "    // TODO\n",
       "};\n",
       "\n",
       "\n",
       "// Map slider position x to scale y using the function y = a*exp(b*x)+c.\n",
       "// The constants a, b, and c are solved using the constraint that the function\n",
       "// should go through the points (0; min_scale), (0.5; 1), and (1; max_scale).\n",
       "var scale_from_slider_position = function(position, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return a * Math.exp(b * position) + c;\n",
       "}\n",
       "\n",
       "// inverse of scale_from_slider_position\n",
       "var slider_position_from_scale = function(scale, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return 1 / b * Math.log((scale - c) / a);\n",
       "}\n",
       "\n",
       "var increase_zoom_by_position = function(root, delta_position, animate) {\n",
       "    var scale = root.data(\"scale\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\");\n",
       "    var position = slider_position_from_scale(scale, min_scale, max_scale);\n",
       "    position += delta_position;\n",
       "    scale = scale_from_slider_position(position, min_scale, max_scale);\n",
       "    set_zoom(root, scale, animate);\n",
       "}\n",
       "\n",
       "var set_zoom = function(root, scale, animate) {\n",
       "    var min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"scale\");\n",
       "    var new_scale = Math.max(min_scale, Math.min(scale, max_scale));\n",
       "    if (animate) {\n",
       "        Snap.animate(\n",
       "            old_scale,\n",
       "            new_scale,\n",
       "            function (new_scale) {\n",
       "                update_plot_scale(root, new_scale);\n",
       "            },\n",
       "            200);\n",
       "    } else {\n",
       "        update_plot_scale(root, new_scale);\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "var update_plot_scale = function(root, new_scale) {\n",
       "    var trans = scale_centered_translation(root, new_scale);\n",
       "    set_plot_pan_zoom(root, trans.x, trans.y, new_scale);\n",
       "\n",
       "    root.selectAll(\".zoomslider_thumb\")\n",
       "        .forEach(function (element, i) {\n",
       "            var min_pos = element.data(\"min_pos\"),\n",
       "                max_pos = element.data(\"max_pos\"),\n",
       "                min_scale = root.data(\"min_scale\"),\n",
       "                max_scale = root.data(\"max_scale\");\n",
       "            var xmid = (min_pos + max_pos) / 2;\n",
       "            var xpos = slider_position_from_scale(new_scale, min_scale, max_scale);\n",
       "            element.transform(new Snap.Matrix().translate(\n",
       "                Math.max(min_pos, Math.min(\n",
       "                         max_pos, min_pos + (max_pos - min_pos) * xpos)) - xmid, 0));\n",
       "    });\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var min_pos = this.data(\"min_pos\"),\n",
       "        max_pos = this.data(\"max_pos\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"old_scale\");\n",
       "\n",
       "    var px_per_mm = root.data(\"px_per_mm\");\n",
       "    dx /= px_per_mm;\n",
       "    dy /= px_per_mm;\n",
       "\n",
       "    var xmid = (min_pos + max_pos) / 2;\n",
       "    var xpos = slider_position_from_scale(old_scale, min_scale, max_scale) +\n",
       "                   dx / (max_pos - min_pos);\n",
       "\n",
       "    // compute the new scale\n",
       "    var new_scale = scale_from_slider_position(xpos, min_scale, max_scale);\n",
       "    new_scale = Math.min(max_scale, Math.max(min_scale, new_scale));\n",
       "\n",
       "    update_plot_scale(root, new_scale);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragstart = function(x, y, event) {\n",
       "    this.animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    // keep track of what the scale was when we started dragging\n",
       "    root.data(\"old_scale\", root.data(\"scale\"));\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragend = function(event) {\n",
       "    this.animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "var toggle_color_class = function(root, color_class, ison) {\n",
       "    var guides = root.selectAll(\".guide.\" + color_class + \",.guide .\" + color_class);\n",
       "    var geoms = root.selectAll(\".geometry.\" + color_class + \",.geometry .\" + color_class);\n",
       "    if (ison) {\n",
       "        guides.animate({opacity: 0.5}, 250);\n",
       "        geoms.animate({opacity: 0.0}, 250);\n",
       "    } else {\n",
       "        guides.animate({opacity: 1.0}, 250);\n",
       "        geoms.animate({opacity: 1.0}, 250);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.colorkey_swatch_click = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    var color_class = this.data(\"color_class\");\n",
       "\n",
       "    if (event.shiftKey) {\n",
       "        root.selectAll(\".colorkey text\")\n",
       "            .forEach(function (element) {\n",
       "                var other_color_class = element.data(\"color_class\");\n",
       "                if (other_color_class != color_class) {\n",
       "                    toggle_color_class(root, other_color_class,\n",
       "                                       element.attr(\"opacity\") == 1.0);\n",
       "                }\n",
       "            });\n",
       "    } else {\n",
       "        toggle_color_class(root, color_class, this.attr(\"opacity\") == 1.0);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "return Gadfly;\n",
       "\n",
       "}));\n",
       "\n",
       "\n",
       "//@ sourceURL=gadfly.js\n",
       "\n",
       "(function (glob, factory) {\n",
       "    // AMD support\n",
       "      if (typeof require === \"function\" && typeof define === \"function\" && define.amd) {\n",
       "        require([\"Snap.svg\", \"Gadfly\"], function (Snap, Gadfly) {\n",
       "            factory(Snap, Gadfly);\n",
       "        });\n",
       "      } else {\n",
       "          factory(glob.Snap, glob.Gadfly);\n",
       "      }\n",
       "})(window, function (Snap, Gadfly) {\n",
       "    var fig = Snap(\"#img-46d68afd\");\n",
       "fig.select(\"#img-46d68afd-5\")\n",
       "   .init_gadfly();\n",
       "fig.select(\"#img-46d68afd-7\")\n",
       "   .plotroot().data(\"unfocused_ygrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-46d68afd-7\")\n",
       "   .plotroot().data(\"focused_ygrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-46d68afd-8\")\n",
       "   .plotroot().data(\"unfocused_xgrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-46d68afd-8\")\n",
       "   .plotroot().data(\"focused_xgrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-46d68afd-37\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-46d68afd-37\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-46d68afd-37\")\n",
       "   .click(Gadfly.zoomslider_zoomin_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "fig.select(\"#img-46d68afd-39\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-46d68afd-39\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-46d68afd-39\")\n",
       "   .click(Gadfly.zoomslider_track_click);\n",
       "fig.select(\"#img-46d68afd-40\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-46d68afd-40\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-46d68afd-40\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-46d68afd-40\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-46d68afd-40\")\n",
       "   .drag(Gadfly.zoomslider_thumb_dragmove,\n",
       "     Gadfly.zoomslider_thumb_dragstart,\n",
       "     Gadfly.zoomslider_thumb_dragend)\n",
       ";\n",
       "fig.select(\"#img-46d68afd-41\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-46d68afd-41\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-46d68afd-41\")\n",
       "   .click(Gadfly.zoomslider_zoomout_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "    });\n",
       "]]> </script>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "Plot(...)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m = mean(chn2[:m])\n",
    "s = mean(chn2[:s])\n",
    "l_simple_g_mean = layer(xintercept=[m], Geom.vline)\n",
    "l_simple_g = layer([x->pdf(Normal(m, sqrt(s)), x)], -15, 15, Geom.line)\n",
    "plot(l_x, l_simple_g_mean, l_simple_g)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A even better model - mixture of Gaussians\n",
    "\n",
    "$$ \\sigma^2_k \\sim \\textit{Inv-Gamma}(2, 3),  \\mu_k \\sim \\textit{Normal}(0, \\sigma_k), k = 1 \\dots K  $$\n",
    "$$ z_i \\sim \\textit{Cat}(K) , x_i \\sim \\textit{Normal}(\\mu_{z_i}, \\sigma_{z_i}), i = 1 \\dots N  $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "g_mix (generic function with 2 methods)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "@model g_mix(x) = begin\n",
    "    s = Vector{Real}(2)\n",
    "    m = Vector{Real}(2)\n",
    "    for i = 1:2\n",
    "        s[i] ~ InverseGamma(2, 3)\n",
    "        m[i] ~ Normal(0, sqrt(s[i])) \n",
    "    end\n",
    "    z = tzeros(Int, length(x))\n",
    "    for i = 1:length(x)\n",
    "        z[i] ~ Categorical(2)\n",
    "        x[i] ~ Normal(m[z[i]], sqrt(s[z[i]]))\n",
    "    end\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Turing]:  Assume - `s` is a parameter (ignoring `s` found in global scope)\n",
      "  in @~(::Any, ::Any) at compiler.jl:56\n",
      "[Turing]:  Assume - `m` is a parameter (ignoring `m` found in global scope)\n",
      "  in @~(::Any, ::Any) at compiler.jl:56\n",
      "[Turing]:  Assume - `z` is a parameter\n",
      "  in @~(::Any, ::Any) at compiler.jl:56\n",
      "[Turing]:  Observe - `x` is an observation\n",
      "  in @~(::Any, ::Any) at compiler.jl:35\n",
      "[Gibbs] Finished with\n",
      "  Running time    = 11.446022354999997;\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Object of type \"Turing.Chain\"\n",
       "\n",
       "Iterations = 1:125\n",
       "Thinning interval = 1\n",
       "Chains = 1\n",
       "Samples per chain = 125\n",
       "\n",
       "[1.0 1.0 … 2.0 1.0; 1.0 2.0 … 2.0 2.0; … ; 1.0 2.0 … 2.0 1.0; 1.0 2.0 … 2.0 1.0]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chn3 = sample(g_mix(x), Gibbs(125, HMC(1, 0.2, 4, :s, :m), PG(50, 1, :z)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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4yRhr451DVHV1IIB9wDuH2OjIqc+a9scQHjUe1f95A+OueCnja6ed8hWUbO3+177JE9DUNMmkhHnoCBo/QyLrI0kjm1xzcWTzkhNLEjr8gf5DfO3Qj6K2/rYES2OENdv3mBFRkoZDXrkwYOXKrS5NC8zinUNUPp/PpqqhM3nnEBURsaamgNyhMwO/PzCbdwZTFOxeCTCG6ncuGvR7pn63u7Ji3VL0jS/HhjVX5TBd3jpixs8QmVkfObkwwOmkUUTse7xziCqRKHUB9APeOUTV0ABFUZg8WyQjZeSfDbFyz1EIV9RifFM7ym5YbOStb0UrAHuPjv1T5dqvQzoCxs+wmFcfObkwgLFkP2NYxDuHqMaOtcYAvMU7h6hSay4gF5xloCj0Bu8MOWdNLgaLA1NfOs3oWxWF3kDl+p8jWmrH+/5rc5Aurx0R42cYZH0kaaSTay6OTG9SCRp1HS3+zWlfM5jtv1f0JLF6t9wiXBKWvHJhwKpVrSWaFriCdw5Rtba2Ovz+wLW8c4iKiBS/P3QD7xwiU9XAt3hnyKkCPA6wOBrcxw/l7f+tT8WGlxCuKEDbqjlZzZfnRvz4GSYz6yMnFwbY7Y4iInYJ7xyi6uyEgzF2Ge8compoAGOM5OQ0AyLlSt4ZcoowF8BLqGeJIb39QH2On3klLFHC/qMzP8J6hBnx42eYzKyPnFwYEImwfYyRPLgsDat1fxhgD/DOIaq6Oui6TnLBWUb6yF3wuiQ5H4AdCoax6Pmg+pQFW9Azfgw8Hvvww40UI3j8ZIWsjySNbHLNxZFn5f4+rNoTPuzrBnvketurx8CrE9ateyUb8SQpm+SVCwNWr95W7vcHf8I7h6h8vu0Fqhq8l3cOURGRoqrBh3jnEJmqBh/mnSEnFtEkxEoKMLZp1XCa+Uh9ply6FQV7IuieOPi9Mka4ETt+ssTM+sjJhQE2m+5gDCfxziGqRKLPCsDNO4eoGhrAAEznnUNkROxU3hlyorjj71DiQNXKuuE084n6jG57ArESKzasOGtY+UaIETt+ssTM+sjJhQFtbcfsYiwhN9FKY+bMKb02G8mnIdKYO5clEwl8jXcOkRGxkbngNVrmRlmgB6x+WFt3f6I+U8+4FSyRwO5Tbx5WvhFixI6fLJH1kaSRTq65OHIs2zcbXiLsenFwi50Hu+bif69/HV7aO9R4kpQL8sqFAU1N7RNUNSiPFE9j1arWElUNyh3g0vB4yKKqQUPbPR9p/P7QEt4Zss6ReArWMFD58l3DbeqQ9SH8HMAo/Idqh9t+vhuR4yeLzKyPnFwY4HAkdQByV7w0ysqSBKCXdw6xkaxPBoxRD+8MWRcpm4LRW/aCNcSG29Qh63MOWw1QD1x9vxpu+/luRI6fLJL1kaSRTt4WOTKs7qqDlwh7n/7xoN9j9LYIAPiDW7EsqhuNJ0m5Iq9cGODz+WyaFqzmnUNUHg9Z1q7dOoV3DlEREVPVzcfxziEyTdsypG2xhUWxX8LWB4y67pfZaC5tfYraf4SEnaF1xeXZ6Cdfjbjxk2Vm1kdOLgxQlMoxRLifdw5RTZzYVmixJB/hnUNUDQ1QAMvveecQma5bnuKdIatio6pQ0t4FhqxcVUhbn6lnPQdLDOgbf0TvkDvixk+WmVkfObkwIB5XokRYzzuHqKzWwgQAlXcOUQ0cud7EO4fIGKO1vDNkTWPfaUhaFYzTnstWkxnrU7B7L/rGVmWrr3w0osZPDsj6SNJIJ9dcjHzvdbyHZRECfafE0PuGsuYCAFrfewheImxecrLh90pSlskrFwb4fNsLNC10Lu8comppabFrWuDzvHOIKrXmIiS3as5A00IX886QNZGSWhRtD4M91p2tJjPWZ+rpt4PpQKTyyWz1l29G1PjJATPrIycXBihKooyIvsk7h6h6euxOIjafdw5RpdZc0K28c4hM13E77wxZsZTGQ3dYMabFm81mD1ufgs4wusfNyGaf+WTEjJ8cMbM+cnJhgMPh7GZMkZtopVFejihj7FneOURVVwedMfoD7xxio5HxW7eu3wzohKOWZnlb7sPUp3jHUkRLbaB6a3b7zRcjZPzkjKyPJI1MH6yaB9+2nWhM9mIx9cFLi7GYruQdS8qyRmrBYhra4u+hrrkAgM3LJ6KRCJt8vx7S+yUpS+SVCwP8/kCZpgXlbZE0AoGAU1WDC3jnENJG7wy8uyeCD2c+iUh5JVi8Fwq6QDgeDM9jRV8cG5uu5x2TN00LjozL2oTjwPBKtps9bH0mn9kOa1hH79irst13Phgx4ydHzKyPnFwYQGQpIIJc0JnGrl0JO4DP8c4hnE3v/Qg7z1qDRJH962ObAzjTpUB3PAEdi3AOOwrj3r0Yljiwo/ZPaGl5kXdcnnSd5f+CvEV0MQArXHg8200Pqj4Fu3ahr6Ii233ngxExfnLIzPrIyYUBxcXRTkWxyE200giHp/QT0bAPZxpRNqx5ADtm3I+CPf1Tzlzs+n6irO4Tr/nUGf/ArDIbRrVtw+4Tv4L1G9/hkFQIROw23hmGrXDvvbBFCLPYrmw3Paj6FHY8Cd3JEFo+Ldv9i25EjJ8ckvWRpJFg8/Ivo1EnrNnxyUcR0+1zsX7DBniJ0LLuiD+EKm8tj8SgtYWH/P7hrLk4oDFJaGmRJ4RK3MgrFwZoWlulqgYe5Z1DVC0tHUV+f1A+DQEA29+owPYZf4O9N4kZT44GUmevaFrw+YzvO+nEE1GytRsdJ96B99cecbeYVDWY309jvUklSDhsGNW2JhfND7o+zv0x9FaelosMIsv78ZNjZtZHTi4MSCbtVoBV8s4hqp6e/QpjGMc7hxC2nbYFuoVhjK8GrD5x4K+JMP6w753+57Gw9+voPOGfOc0oICI2gXeGYSnrvhkg4JjV9+ai+UHXx9azDOHRtlxkEFnej58ck/URFBEpmrazkHcOURERa2npKOKdg7v31zwMLxE2+p74+Jc2btxYDODw238HvJeiUSdobUfUWST/rU++WtXZjpX7aFhtZLgtMuj6vEMnYjER3qFThpUlz+T9+MkxM+sjr1xIUjYFvGXoqLkFRbt6ccKMG4fcTvWcV1GxYQP2HVuLjb45WUwo5VK0eAJKPuzhHQOfZRvAEIUC+ei8xIWcXBjg928dRxT5I+8colq9uq04Hu8/su957q/ygyxAhf8Th0d5PGSJRJyvDbqtaSedDGuE0FX9j6xmFFg47Mrf/9e36BjoNgvGbMjqlt8HM1ifjWA4L1dZRJTX48cEZtZHTi4MicaJWIB3ClG5XMVJxlgb7xzctK84CV2TqjCqVUX1BcGPfzl15Dr7YNDtMegYqy5EeHQBNvjvyGZUcdHg6yOaon0/AtOBynX35a4TA/Upb+sAS56QuywiyuPxYwpZH0nKP0vD72FpPDGocx2MHLm+ujOG5X2Jw79Q4mpl1y6s3qMPu51sPIoKAAHvbHiJsGm5vDUimU5euTCgtbXV0dy89ROXu6UUr5esfn/AzTsHF0uoGknnDMB6x8FPhxyMiFhzc+hUw22Pa5qPeIEFzc0PDDun4Jqa2vP3RM9EUQWKt3XlsgtD9ame0whLHIhUZvnwNHHl9fgxgZn1kZMLA3p6HOW6nvwx7xyicrnaChhjOXkET3g6/gygF2exR9K9pKEBiq7Tg4bbnnTeH+Dc14N9J9wwnIj5gDHKzwO3llA1EhYF5ZsW57Ibw/VxdIXRXzE1R3GEk7fjxyRm1kdOLgxgLNnPGBbxziGqsWOtMQBv8c5hutZ3TgRwNhgyThxSay4wtAVV4VHnQbeNwjt0+ZDenycUhd7gnWFIbL23QkkClarxyaMBhutTsHcdYiX2HMURTt6OH5PI+khSPlkb2oElMQLR4CfrRtZc/O8978NLW4zGk0ywons7VncOf70FkL01FwDQ1ngBFhNh8/IvZ6U9SRokeeXCgFWrWks0LXAF7xyiam1tdfj9gWt55zBVi6cIPUePw+hAMxjL+MOFiBS/PzT0Wxs6vg+gGi1t5wy5DcGpauBbvDMMSdI1FqVbP3mGTJYZrs+U2f+CJQH0VxwRt3PzdvyYxMz6yMmFAXa7o4iIXcI7h6g6O+FgjF3GO4ep9Gn/ATFA2X7Yc0AaGsAYo6FPTs9lb8AWJvQVeYbchuCIlCt5ZzBsEU1C0qqgYuPbue5qSPWx74+ir/yIOCE1L8ePicysj5xcGKDr1i7GmNxEK43i4liEMVrIO4ep9h87E8U792HanJ2He2ldHXSAPTys/kZvWov+ynL4fBXDakdQioKHeGcwTMF1ICRQ8dW5Oe9qKPUp6tyIaJkzB3GEk5fjx0SyPpKUDzb47oWXCK3L6gy/dyhrLgAg8HQZGhMELZiTUzelIfDSu2ik7G0el801FwDQuuIqLCZCYPmsrLUpSYchr1wYsHr1tnK/P/gT3jlE5fNtL1DV4JHzKGrvpFth705i6mcaBvNyIlJUNTi83xyqr+tC2Yf70D3O+H4ZeUBVg8O7ssMD4UQQ3jWjqyHVZ+qn/wpFB/pLR/xnMy/Hj4nMrI+cXBhgs+kOxnAS7xyiSiT6rACOjE20Wrzj0FdegLLAvwf7loYGMADTh9136aZbkXQwrNv43WG3JRgill+TpjepBAwlOGZVuxndDbk+jt4E+secluU4wsm78WMyM+sjJxcGtLUds4uxxPd45xDVzJlTem02GvEbPQEA9HH/BCOgY9+g952YO5clEwl8bdh9V5//DOy9OvrLfzbstgRDxPLraawC/VqAgMmLTDmzYcj1cXTuQKS0JMtxhJN348dksj6SJLrl/Un4Ptw75PcPdc3FAe+vfReNOqGlpWjIbUjD926XihU9BJpXkLU2s73mAgA2rnkEXiIEvGVZbVeS0pBXLgxoaQmMU9WgfFokjY0bNxaranDkH7netvwaxF0Kird938jbPB6yqGrg9axkGLX4iwABSceIeixVVYP5dWR2wnk8inbGwZ7qN6O7IdcnGbgLDED30SP6nJG8Gz8mM7M+cnIhSUb1TPoVrBHC8TP5TTTH3dGBwo4IesZ+lluGI109WZGwOzEqEOQd5bCmze0FoRN7p5zCO4okSZJ0KEviBK1teI8eDve2CAAEvE/DSwS19YjYIEk4XroUXiKEH7w/y+1m/7ZIql0vFtPWrLcrSYcgr1wY4PP5bJoWrOadQ1QeD1nWrt06hXeOnNrguxe6FSj88GqjbyUipqqbj8talqolN0BJALp9xNyK0rQtx/POMGi2nnmwRAHn/j+Z1eWw6kN4GwrGZzGOcPJq/HBgZn3k5MIARakcQ4Ts/pYygkyc2FZosSTTHjk+IvRMvBH2viSmnL3S6FsbGqAAlt9nLQurT6Bk6z70jR0xVy503fIU7wyDp/wfCvcQ2H2bzepxWPWx7H8ROiz4YM2IfWIgv8aP+cysj5xcGBCPK1EirOedQ1RWa2ECgMo7R84QKegfU4qE/fGhvH3gyPWmrGYa0/IgEg5lpBxmxhit5Z1h0BKuUhRv3Wdml8Oqz9llAVgSQLT41ixGEkpejR8OZH0kSUSL6Do0ko6VNHrYbWVjzcUBSyOEpm2bstKWNDjv0InwEmH/H7Pz9M/BcrXmAgBW7YvivY7ctC1JB5FXLgzw+bYXaFroXN45RNXS0mLXtMDneefIGQU3Qkc7zmBD2t8iteYidFG2Y8GaeAddR43LerscaFroYt4ZBsUWvx5KEigJPmNmt8Ouj2vvVkRLXVmKI5y8GT+cmFkfObkwQFESZUT0Td45RNXTY3cSsfm8c+QE1VvB9Blw7P/PUJtIrbmg7F+SjhbeAYYSNFLeb++s67idd4ZBscUvhWM/gE2m7qsw7Po4Oz1I2Bk2vjYhS5GEkjfjhxMz6yMnFwY4HM5uxpQRszI/28rLEWWMPcs7R05suugJkMJwtO8XQ22irg46Y/SHbMYCAMxhKoAuEH6c9bZNR0/yTjAocdtEFO+MgjXEzO14mPXZ3pfaMp4m3peNNOLJk/HDjayPJIllzc4erOhOZK29bLB85XUAACAASURBVK65AIDlvW9jSSKStfak9HxUgEYifPjqxpy0n8s1FwCwvF9HU/DDnLUvSZBXLgzx+wNlmhaUt0XSCAQCTlUNLuCdIyf6K4pQ8qE2nCYGjlzPzUr9qqXLoFscULefmZP2TaJpQfEva/fiMhCAyvUvm911Vurj6OpBdFRlFuIIJy/GD0dm1kdOLgwgshQQQS7oTGPXroQdwOd458i6Db57oVuAop3fGE4zA0euZ39BJwAcdeHPYYkBSf13OWnfJLrO8mFB3iVQkr2wwvRaZ6U+Bfs0RIusWYgjnDwZP9yYWR85uTCguDjaqSgWuYlWGuHwlH4iuot3jqzrH3cj7P06qucMaw+PujroisLuyFasj2DQUby9B/3lJ+akfZMQsdt4ZxiEGdAtKtidpt9ayEp9nHt/BVKA1pUj7heBPBk/3Mj6SJJIlkQJ2ubhnSXycdlecwEA7f/+HbxE0LrlFsi51EgxeKk+Z+3nes0FADQmCS3rF+W0D+mIJq9cGNDU1DrG7w/JKxdpaNrOQk0Ljaztv1tXfB26HSj8cNj3KlNrLkLZ2/77445ZdSuUBJDYx++01mHy+4PZf5omm96hE0Gwwd77Nx7dZ60+tr4kwqNPzUpbAhF+/HBmZn3k5MIQh40xkgeXpREO91iIaGQdXNY7/j5YY4QpZ7063KZSay4oeweXfRyrj6CgI4Lo6NNz1kfOsdzVJxsU/WtgSeCMX3FaOJul+rj27UakrDgrbQlF8PHDnXn1kZMLA2prj9nJmFM+LZLGzJlTemy2gpF1KFL/2GNQ0NGZjabmzmVJpzPyxWy0ldboLSsQK7LDQ0U57SdHXK5wbha8Zostcikc3QAsXK5cZK0+zk4vEk4FVD+iFnYKP344M7M+cnIhSem8v+w4xAoUFO8y7UjtYStfdQNAwNTAyLo9JQrdOhklO5Ng9Xt4RxmWwr13ghjQev4tvKNII5OcXBjg928dRxTJ2/vZubZ6dVtxPN4/cnYwTZQ/DaYDx834YTaa83jIEok4X8tGW2mV3RGAsyuJWFldTvvJkXDYZep22obUkxVkd6C0bRevCFmrz6TPbgHT4+ioHVGLf4UePwIwsz5ycmGAxRJLANTBO4eoiotLdSLs5J0ja/rGzoBzX1Z3vWQMO7LZ3iGVBjcjXFqa835ygDHazjtDWmfhCyAAY1q8vCJktz5KG+LO6dlrjz+hx48AZH0kiTeqt6JRJ7Q0v5OT9nPxKOoBnc9cBi8R3uu4LiftH6kak89iaZRAd345p/2Y8SgqADTSs2ik/TnvRzoiySsXBrS2tjqam7eezDuHqLxesvr9ATfvHFnxfl09wABn9/XZapKIWHNzKPeP/5Vf+zJsYQL0O3PeV5Y1NbXP4J0hLWvsXLg6AVjf5BUhq/VJ4A0QStDSkpeLfw9F6PEjADPrIycXBvT0OMp1PTkCTp7MDZerrYAxdi/vHFmx68SZADow+cz2bDXZ0ABF1+nBbLWXUfG2bkTLqkzpK4sYo1/zzpBWwj4OpVtjYPXcDojLan3GN/wbAKD0/yxrbXIm9PgRgJn1kZMLAxhL9jMGuatdGmPHWmMA3uKdIysIp0NHVu+t19WBAJizoKpiUwMSDgVLuvJqXxZFoTd4ZzikVTQWpFhQvinIM0ZW6zNtbi+sUUJs9CVZa5MzYcePIGR9JImnJVQNLxHeoTk56yOXay4AgL5TgkaKoZEezlkfRxIv3YxGnUD1vzWhL3PWXADA6o4+rOqMmtKXdESRVy4MaGnpKNK09hEzy8+21tZWh6aFLuedY9gK258E9CQ+y7J65YKImKYFzNlkjD3WDYIGQl6NV78/eCXvDIekxC+EtQ+AnttHiQ8j6/Up2NeGaLE9q21yJOz4EYSZ9ZGTCwOi0UgJkT6ydqDMos5OOIjoGt45hi1eOhsF2f9trqEBChG7IdvtZvASGKpBlEefc/Yt3gkOidFpKN5NwM+4PYY6ECS79XHseR66DQi8W5XVdrkRdPwIw7z65NE3Hf503drFGJObaKVRXByLMEYLeecYFqq3IlJiQ+Gu5dluuq4OOsDMu00RxlMgKFjd/W3T+hwmRcFDvDMcUtJWirJgPxh0njGyXp+p/3kYICDiuCer7XIi7PgRhKyPJPHy/pqH4SVC6J1jc9pPrtdcHLC8h7BqVyDn/YxkXnLDS4T+x9aY1J95ay4AYFm/Dn9wq2n9SUcEeeXCgNWrt5X7/cGf8M4hKp9ve4GqBvP7UdRw5ddgC+uY9Nkt2W46deR60NzfHIp37EesdKKpfQ6DqgbFW4Cq4KtgSYKrs4F3lJzUx9Hdi0jZ2Ky3y4GQ40cgZtZHTi4MsNl0B2M4iXcOUSUSfVYA+b2JVl/lGBTuzsnZEakj12HudsuVLa8j6VCwiCaZ2u8QEbHcbzJmFOFskGULWP2vuEfJRX1cXe8jVmjLerscCDl+BGJmfeTkwgBd79jNGOQmWmm0t0/pSyYt+XvK4vvLjkPCyeDq+HMumk+tuUiau/5h3JofQEkCJTvz4l6roiTn8c5wCMeD4OMdAshRfQp2P4mkFQh48/sXAwg7foQh6yNJPLSsX4TGJJnSl1lrLgBg9a4EVu7vNqWvkaaerGgkHY10lWl9mr3mAkDqHB3tb6b2KY1o8sqFAS0tgXGqGpRPi6SxcePGYlUN5u+R631jZ8HZHctV8x4PWVQ18Hqu2k9rVHsQsaJi0/sdAlUNinVkduokVIbTH6ngHQXIYX1sYR3R0jNz0raJhBs/gjGzPnJyIUkHhMsKUNixgXeMrBu79lFAAVZ2X8o7St5RcAksMcDVVcI7Sk45uroRHiXEBEqSJGnkaF1xORYTIbjkQlP6M/O2CNXZsSxMWN3RZEp/I8mSRCvWbCdQ/Ymm9cnjtkjLhiVoTJhzS1A6IsgrFwZ4PGTRtLZK3jlERURKS0tgHO8cQ9I35l5Y40DV2Tk9TtvnC47PZfuHxBpiKN4RQbx4mul9G9TU1D6Bd4aPIDYJJdsIrF6IK1o5q49z76MgC7By68k5ad8kwo0fwZhZHzm5MGDKlK1jiayP8s4hqtWr24ricfYH3jmGpL9yClx7e3PZhcdDFqsVz+eyj7TK2tYi7rTjTRL68j5jJM6anZU0GqTYULGpk3eUA3JWn8ln/h1AEpGjL8hJ+yYRavwIyMz6yMmFAfG4EiXCet45RGW1FiYAqLxzGEb1VkRLrCjYtSyX3Qwcuc7n1sSklXeCEVDWdTuX/geJMVrLO8N/9aMOIGB0QJjbSTmuTwcYZuew/ZwTavwISNZHksy0yfcLeImwebl5O1mauebigFVdOt7du83UPvOZl17B8j4C/fRHJvdr/pqLVL/vwEtyG3ApK+SVCwN8vu0FmhY6l3cOUbW0tNg1LfB53jkM2zH9RCh6Dyaf2Z7LboiIqWroolz2kVFx+37Ei81f82GApoUu5p3hvxT9dBR2AAgLs/9DTutT2PEBmH5Uzto3gVDjR0Bm1kdOLgxQlEQZEX2Tdw5R9fTYnURsPu8cxrFZ0JWsn4L6cQ0NUAC6Ndf9pFW57p9IWBWspBO4ZTgMXYc4t22IjUNZKAn2YCvvKAfktD6jNr8GUphpT0zlgFDjR0Bm1kdOLgyIxaK9jJH5myDlifJyRInoZd45DPFRAQhjwJDzhU51dSAixm/BWYX/Lih6EhHcxC3DYTCmv8A7AwBgJZ0AYgoqN+zmHeVgOa3P1DPeAtOBvlE356yPHBNm/AhK1keSzLJm+8/hJR0espvaL481F6l+m7CYNpneb75ppHvQmCBQ/T9N75vXmgsAWNGTgO/DPVz6lkYUeeXCAL8/UKZpQXlbJI1AIOBU1eAC3jkMYfpNsPfqmMtytu33AQNHrvO7LQIADK8AmMw1QwaaFhTlsvZs2HsA6It5BzlYzuvj6tqHSGlZTvvIIYHGj5DMrI+cXBhAZCkgglzQmcauXQk7gM/xzmFIf0UpCnab8gTFwJHr/BZ0AkAUT4LBAi8JufBW15kYC/KYfgqKdwBICrOYEzChPo59PiRclpz2kUPCjB9BmVkfObkwoLg42qkolvt55xBVODyln4ju4p1j0FrfORG6g6Fo1xNmdFdXB11R2B1m9JXW+d/qhTUCOPf9hGuONIjYbbwzgEgBKaUYvSUB9vMQ7zgHy3l9lM4HQAqwefmXc9pPjggxfgQm6yNJZmhpfse0I9Y/jteaCwDwb4ljWX+YS9/5YBGdDy8RYg/wmVjwXHMBAI1Jwvr1Qt0OkvKPvHJhQFNT6xi/PySvXKShaTsLNS30CO8cg9ZbOQuO7rhZ3aXWXIR+b1Z/aY1ua0XC5YSXnLyjfJzfH+S/fbyCL4FRBLaeb/GO8nGm1MfWl0RklDvn/eSAEONHYGbWR04uDHHYGKNq3ilEFQ73WIhoCu8cgxYdXYjC3W1mdZdac0HHmdVfWuNX/Q4gwBK/jneUT2L868PwaYC1gt33b95RPsmE+jj270W0tDTn/eSEAONHaObVR04uDKitPWYnY075tEgaM2dO6bHZCq7gnWNQ2pbPQcIGFHQ8YFaXc+eypNMZ+aJZ/aVl0/8Iey9gDQv3ZI/LFea74BUACMeCsJJ3jEMxpT7OvasQL8jLnw1CjB+BmVmfvBxAkjRs4YpfwpIEppz5LO8opmP1EZRtjSLulL/lfZyXygAUwr73Hd5RuLF3/hzEgA9W5scvCpKQ5OTCAL9/6ziiyB955xDV6tVtxfF4f34cedxXcQqc+6JmdunxkCUScb5mZp9pVbT4odutWEVjeUc5WDjs+gfnCJcDBJzx+K845zgkU+pz3DmroSSBeOmNOe8rywQYP0Izsz5ycmGAxRJLANTBO4eoiotLdSLs5J1jUCJlThR0rjO7W8aww+w+D6lyw2NgOhCJfY93lIMxRts5R7gQtggBSZVzjkMyrT7W/gTCo04xpa8sEmD8CE3WR5JyacvyuVhMhNaV/Db84vkoKgBQvRWr9hCW9+T0JNi8s5hC8AcJdNe3uWXg/SgqAKwN7cCKviTXDFJek1cuDGhtbXU0N289mXcOUXm9ZPX7A+I/wtY75m5Y4qmDmkxERKy5OXSqmX2mxeoTKAv2IekS6ojtpqb2GVwDMDoKZVsAhP/ONUcaptWH6AXECpgpfWUR9/EjODPrIycXBvT0OMp1Pflj3jlE5XK1FTDG7uWd47D6K6fA2dVvdrcNDVB0nR40u9+0JqjLkLQo8JIwE0LG6NfcOl9JJwDMgsqWGNhDQt7+NK0+/ZMeAoFhMc00pb8s4Tp+8oCZ9ZGTCwMYS/YzhkW8c4hq7FhrDICpVwOGJFJiR9Een9nd1tWBAIiz4Kz4w9/BEgeskVt4RzlAUegNbp1H8TUwnVCwR9hbRabV5yy2AwxRWPAlU/rLEq7jJw+YWZ+8u+wFAN+//vrivqTrAsZYzNZne+uRhkc+sZVxutfcdO1Nn1egFB94Xcwee/Wpp54ybZdGibOlvZ9DsvDfGL/iNJxwpukTjP/y0t0gTMY57GpuGQgKfNuSiI7uxJkFFdxyiKKRVsCxfyZmPfIK2D113HJ46SQwrMZsVsgtAwAsps2wJPbgbFteXb2QxGDKlYu5F8y9a+6Fl9958N999aLLZ8+98PKX6urqXEbamjdvnq1fdy0DUAfgvHhB9HUjr2FgTwD0mQP/xWKxQZ8A2NLSUaRp7ZcYyXskaW1tdWha6HLeOTLSC68E0MtjYkFETNMC4uwdwKCjfPM+JJyjeUc5wO8PXsmtc6JPoeRDBaC3uWU4DFPrU9ZuhzWeV2sYuI6fPGBmfUyZXDBF7wLYjy6++OKCA3+n65gHsIqGhgZDByjZ4/avgCG08NmFdY8/8/h8MFax4KoF1YN5zfyr55eDIfD4Mwu/e+C/Z555JjLYvqPRSAmRLs4PB8F0dsJBRNfwznEYZ0GH6Y+gAqk1F0TsBh59pzVh7V9AjGERCXJUNeNznoeH7AArQ/kmBvS8zCXDoJhYH2fnMsSceXbrnNP4yRvm1ceUgROLJ18CYHclXRcAwLWzr3WCsYsZ6DnDjRGmgZj2vz+z95lVP3VQr7FgCiOMWnDt/LfnXzv/ufnXzD/LSNe6bu1ijMlNtNIoLo5FGKOFvHMcxjFgeJVHx3V10AH2MI++03LeejMY9oHhWt5RAEBR8BCXjkfjEgAMY94Pgz2yl0uGQTC1PqyvHmBA24rvmNbnMHEbP3nCzPpYzejklbdf6Zj7hbq3oeNyAC/3u/o/D4LVSg7jvyEQjWUMyw/8kTHaAWDcYF7DdLaDMVpBCrsfSfoUY2iYN2/etKeeemrPgdf6fD6b3T6mKBazRWfMmNC/cuVWV1GR7nS5Yv1Tp07ob2npWN3cHBq1cePE7rlzWdLvD5QBQG1tdZfHQ5YTTmgvsVhc8WnTKntbW1sd4bC9oLdXiZxxxjFhn297gd0ed8Riu3tnzJgRX7WqtaSgwG45+eSJXQCwbl17WX9/LDlr1tTuAzmIHLGamnF9gUDA2dOjuFI5pkZbWjqKksmwLVMOuz2cOOGEE3paWlrsyWRR4WByMMaouTk0KhZL6DNmTN7v9ZK1vLy9eDA5pk1jMZ9v87vNzaFRp5wyaR8RKevWtZcONsfGjRuLYzGX9eSTJ+5njOlGcmjazkLGovbOzok9c+awhM+3udRutyoH5/g/147v930Iywmjgh5Pc2jUgRwH/o0tlt6+adOmxYzkOPBvXFysh6urqyOZcgBgioIVGzduLD5hB6BAV9Tm0KiPj7XB5Eg31gaTg4jYwWONAT4oOHONb3vBYHIMZsyny3G4Mc8YlvvS5BjMmB/qZ8/lRV1EiSWhRNs//j1gKJ+9AzmMfPYO1OMrneGi9+HCocc8lre2tjrS5bBYFDaUz95BOf431voSu2YoCbD+0ddpzaHnDvc9INNn73A5hvLZO5DjY2NtuddL1sHmGMpn70COIX72lHXr2ks//n3eSI5kUqehfPZ8vs2ljGE5EbF0P28O9GP45/IhmHfJi9hzUOiia2df62SM6hjw2vP/er7beDNoJtB/n83XgdEsiZbBvObxZx9f8dgzCxc8/ufHty98duEiBrzliNk+sobCYql0E5HHao19GwAKC/U6IvL091vnNDeHRsXj/a8SkWfKlMDRAKAoyjMAngWAKVMCRxORJx7vuxMA+vutc4jI43Il5gKA1Rr9FhF5LJZKNwC4XLaHiMizYcPuwnff3eYkIo/TafsNANhsFScTkUfXIzcBQFcXu4yIPL29ts8CQCLR/0Mi8pxwQvskAGCM/Ykx9hwAHH/8h+OJyBMOO38KALFY0dlE5CkoSF6Rajv+TSLy2GzlpwKA02l/gIg8a9duKfH5fLZURuW3AFBaGphGRB6i8HcAoLsbl6bq4fgcAMTjfXcQkWfq1C3Hrly51WWzKct0nV4AgLVrQ2OJyBOJOO9JZS48M1UP/eupWseuS/U15nQAiEScv0jVY1sZESmpfwfLQgAYPXrrCQP1uDlVD+ViIvL09dkuBACi6G1E5CkvD05J1drye13XXwKA5ubNFUTksfRWLoAlSi8QJqXqkbgGAAoKEtcQkSeZdM1K5XDcR0Qev7+tHAB0XX/JarX8HgBKSkJTU/WI3gYAfX22LxCRp7tbuSj12sjNROQZNar9+IEcC1OvJ8Xv31lORL5IxPkLABhr0VO5LLHrUjn0q1Ljp/DTA/W4J1WPYGWqbXrBalWeAoDjjtsyeWCs3QEAvb3WzxORZ/9+DByMFv4uEXkqKgInpmqt/JaIPD6fz6aqwVIi8jgctl8CwExLZDURKvdbEjelciSvICJPNFp01kCOu4nIo2nbxg+MtecOXMH71Ke2VqVy9P8gVQ/7eUTk6epil6UyR+en6hE6eWCsPUpEnmAw6Ni0aVNRasxbH0zVanQtEfkslui81OcjMTfVdsGcgbF2FxF5jj12y1GpHPgLY+xpAJg6NXgMEXlisfCPASActp1DRJ7CQr0u1XbsRiLyKEplTSqH7WEi8jQ37ypYu3aHq8yavEgp2KMA8NntY04Z+B5wIwDs369cPvDZOzf1eQr/mIg8xx8fmjhQj6cZw19S9dg8YeDf5a5UZtfsge8BX0n9O0TnDXz2pqdyWB8kIs/q1W3FbW1tdiLy3Fbc/UMAKCsLnpQa89H5A5+9LxGRr7/ffn6q7f4fEJFn8uRt1QM5/phM0vPAgaMKyBOJOO9OffaKPpOqR/LKVD3i30iNvYrTAMDhsP2SiDzr1rWXer1kHfjsPQZHb4xFRx9PRB4g/N2BelySqof1glQ9+m4nIs/o0YHJqbaVp3QdLwLA+vWBMamx5PpZ6rUFZ6Q+e/pVA98DriUiTyJRPHNgrN2f+l60YzQRsVStLL8DgNLS9uNSn6XU003d3Wzgs8e+kPoeELmViHylpe3Hpdq2PDHw2WMD7XkiEefPU/UonplqO3rge8DVqfFTcEZq/DjuJSLP+vWBMalxjBetVuuTADB6dGByKnP4toHP3gWpMa8M3FqMfC/1vWjbpwa+BzxORB6vl6wD39s8LpftF6mMFacNjLXrAaCwMPm1VNuFZw7Uoz71vWjrOABI/fuyP6TG/JZjBz573weA/n77+al6pJ7wIYouICJPaWlgGgDYbNZHicjX1tZmX7t2S0nqs2f/Vepr5acSkee99z4chSwx7WmRiy++uMClO3cx0A1E7CliuKLhnw3/NNrOgmsWfBqM7nv8mYVzbrzyxlGKXWmCjhkd4Y6uiuKKSU/8+Ykt6V7DGLuUMTrpsWcW3jJv3jybPWZby0j50mPPPrZ5MH03NbVPUBT91253lVx3cQirVrWWOJ22593uKkHu33/Mip4EHD29mDGhjEf3Hg9Zjjsu9B+3u+ocIZ4WOSD6iyvw7g9egM7m4xz2O55R/P7QktraSWeb3nEjRXD0u3ZMfvvrYPUvmN7/wTI8LWJ6fdRAED3jJuIzrrxYe8Ft/OQJM+tj2oB54403+kHs70TsQQDh3X27h7Qfwq7+XasA2vWda+e/Z7Er7yuERxb+ZWFnubO83KIrmzO9xqk7XySGmQuuu+lNe8weAtiywU4sAEDXO3YzBrmJVhrt7VP6kkmLMHsmfAR57IgVWuDa/R9eEVJrLpL8tpVOx97/Aew9gDXGfTGuoiTnmd7pIpoEHQ5UrmMAPvH0mUhMr49r79tIOhm8Xqep/Q4Rl/GTR0ZsfeourDtv7oV1NPeCy4e9S+GC6xdM+P711xcP5TU3f33e+JuvvZnLb68SJ++veRiNRNi0SIztrnmfLfJxLeuSWBo39ZRYYTTSXWjUk6D6Qf+ikVMinC1ywKZFR6GRCBvfvfPwL5YkTi676LKpcy+s0y+76LKpvLMMRUtLYJyqBuXTImls3LixWFWDYh65vja0A8v6s7JQaag8HrKoaiD1m7Fok4u9fwnAS4S36BieMVQ1aP4Opl5aisUUMr3fdDJMLrjUZ0mUoH3A5fFto7jUJ4+YWR9TbovMnj3bWldX57ImldvB8K+X//Fyqxn9Zls0alEA8N01T2BdXRYGoIh3jkMKl1eioFOARwyZmPUZ1fYaFB2w4UaeMYhYxquRuekU08Cw1vR+h4BLfZw9UUTKJpve7xBwqU8eMbM+pjyKOsY5ZjLrw0ZieI9B+YYZfebC9OkTtwOQiznTmDVrajcA8RZztniK0FGgoHwT13MH5s5lSQDn8MyQnvIUXHu/h0jpZQC/dUWmL8arJysUjALwiqn9DhGXxYqOrq3oOSYvJhdyMWdmZtbHlCsX02ZNa1WslqM8bzbMfOmfL603o89c8HjIomltlbxziIqIlJaWwLjDv9JkbMqjYAwo2nwb7yg+X3A87wyHxOo3YNQHSehWrj9EmpraJ5ja4Zm4FASGM+//pqn9DpHp9QEAR9drSNoZAl7h16lxqU8eMbM+pkwu6uvr9Rdff3G7GX3l0pQpW8cSWR/lnUNUq1e3FcXjqWewhRIecwls/TqOmcv1tojHQxarFc/zzJDRBN8HIGbBIjqDVwTGyNw1OxZcCiUehyVaY2q/Q2R6fQDA2vEzEIBI0U9N79sgLvXJI2bWJy+eXRZFPK5EiZC3V15yzWotTABQeef4hHB5OZx7OnjHGDhyvYl3jrQKOl+FJQZYwO18BsbI7LUPs1CwJwkoebEOjEN9gKkXdsMaJcRGC39oI5f65BFZH0nKlhbvOHiJsGnNY7yjfIRoT4sAAN1ejaYgYUliF+8opvFSDFuWxkF3izM+RHoU9YBVe7rxbtd+3jGk/CGvXBiwcuVWl6YFZvHOIarU1tKhM3nn+KjRj4ERsL33Dt5JiIg1NQXEXXDGHgpgzIYYdKUydUqo+fz+wGzTOnuLTgLBhrGqFbD8zbR+h8HU+hwsWv4sIqU2Ln0bwK0+ecLM+sjJhQFOJ40iYt/jnUNUiUSpC6Af8M7xEeEx58HWl8ScORHeURoaoCgKu5t3jozG+zSAAeX4Gp8Ayj2mdWXHNVD0BAr2EPDTZab1Oywm1udgSbwKwIWVNJpL/4PGqT55w7z6yMmFAbFYtJcxEnp7YJ7KyxElIuMn3eZSuKIQzr1B3jGA1JoLIib2gjNL/FXYewGFz+SCMd3Mcz3mwN4bBrAXDFw3WBssk+vzP3PgBUCI4stc+h8kbvXJE7I+kpQNb1AFvERYTBfyjvIJIq65AACqr8D6dYTGZC/vKDnnpR5saO4G1S/nHeUjRFxzAQBLYv14b4dc0C4NirxyYYDfHyjTtGBePA/PQyAQcKpqcAHvHP9ViHkg6DiHvck7CpDaB0RVg7fyzpERq9+Do3x9IKWQx1bgmha83ZSOUpf3izDOXwCg0ZQ+s8C0+hxKYWccCdfx3PofBK71yQNm1kdOLgwgshQQ4VzeOUS1a1fCDuBzvHP8l4KLwSDMmRENDWAALuKd47DKQhUA4nBivtld6zozZ4fXp2QahQAAIABJREFUCL4OBh2jtliAWF4s5gRMrM+hODrXI15kyq7OQ8W1PnnAzPrIyYUBkQjbxxjJTbTSsFr3hwH2AO8c/8Xip6OgU5j9C+rqoOs6ib/gjNVHwLAJxGMrd92cBa8Ml8AS6wWQALtfvL1Z0jKpPofi3P8IdAsQfEvQLewBrvXJC7I+kjQ8bUvOgJcIH6zktiFURqKuuThgEd0HL8V5x8gZL+2Bf0sH6O6tvKN8gqhrLgCgMUlYv+4t3jEk8ckrFwY0NbWO8ftD9/POISpN21moaaFHeOcAAIQrfg2WBI4740neUQ5IrbkI/Z53jkGZ8eRuAFYsovPN7NbvD+Z++3gvOQGMxljNAbDmnPeXRabUJxNbfxLRstO4ZsiAe30EZ2Z95OTCEIeNMarmnUJU4XCPhYim8M4BAOivrIGrO8o7xsFSay7oON45BqVk5/mwRnUo+La5HbPc10fHFWAAxq4rApJ59lu4CfXJxNG1F+FRpVwzZMS5PsIzrz5ycmFAbe0xOxlzyqdF0pg5c0qPzVYgxpH0kTIXXLtaeMc42Ny5LOl0Rr7IO8fgsBdRspUBOMvMXl2ucO4XvCr4EpDcDyWpAMmGnPeXRabUJ5OCzhVIFAj7c4N7fQQn6yNJw7Fl+VwsJkJwiXj7Wxwg+poLqrdi90s6vER4gyp4x8kqL+3A0sQi0E+/wzvKIYm85iLgdQu9lkkShrAzUBE1NbVPUNWg2DsscrRqVWuJqgbf4J0DPWPuhCUBVJ0txP4WB3g8ZFHV4GLeOQaF1SdQsWEHGBEKzHsk1e8PLclpB/VkBTAWCcvLYD8T57CyQcp5fQ6neo4KlgDCo02+XTY43OsjODPrIycXBlgssQRA3I/uFlVxcalOhJ28c6Cv8gS49vbzjnEojGEH7wyDx5bBuZdgMW/LZ8Zoe047mI0vAWCI4Lmc9pMjOa/PYDh6YoiMFnJtgxD1EZisjyQNR2OS0LJ+Ee8YGYl+WwQAqP58tC2nEfVIqpf+jkbqBN0xlXeUtES+LQIA/tY2LIvmxVksEj/yyoUBra2tjubmrSfzziEqr5esfn/AzTXEpvd+BCiAveO7XHMcAhGx5ubQqbxzDBqrfxtHvZeAiY+kNjW1z8hxF7Ng794BFG4C1Qu92+ShmFCfwyvY34CEnaHFO453lI8Toj4CM7M+cnJhQE+Po1zXkz/mnUNULldbAWPsXq4h+sZ8G5YoYeo5Qj0pAqSOXNd1epB3DkOc3QFYowkouMmM7hijX+es8dR6i3EY748CehdYfSJnfeVITuszWNt77gEDYC35Ge8oHydEfQRmZn3k5MIAq5XCRLSadw5R6bozDtAKriEiY45CwZ4urhnSqKsDMcbybMGZ/g7KQgwMnzGjN8b0xpw1Pht1ABiOWl4OsPdz1k8O5bQ+gzVnTgSWCKG//ALeUT5OiPoITNZHkoaixVMEr05oaXqed5TDyoc1FwBA9adgz19o4JHUo3jHGRYvvQIv7QHdHQX9VNyddkVfcwEAK7s/wNL4h7xjSOKSVy4MaGnpKNK09kt45xBVa2urQ9NCl3MLwI77DRgDCvabfprnYBAR07SAGJuMDRarb0b5lggUXUcRbsl1d35/8MocNj8LSmQjQHZAeTGH/eRMjuszeNHil6Bbx/CO8XHC1EdQZtZHTi4MiEYjJUR6fv1wMFFnJxxEdA23AP1jLoGtT0f1HCFvizQ0QCFiN/DOYRxtgGt3HIAJE2uWm82ZPGQHMBYT1E6AJcDq8+pMkf/JUX2MsuKvINjwFp3EO8pHCVIfYZlXHzm5MEDXrV2MsT/yziGq4uJYhDFayC1AzwQbktZ/cev/MOrqoAPsYd45jKNXMbbZDobJA4sic0ZR8FBOGh6DqwEA1e+MAbAtJ32YIGf1Meoz7AMAcbj6vsE7ysGEqY+gZH0kyai3qBJeInjp87yjDEq+rLkAALq9Esn7CF7S4SUhd2Y8rEZahMX0Iai+E3S32OeJ5MOaCwBY2RXDmp09vGNIYpJXLgxobg6N8vsDN/POIaqVK7e6VDXwQy6dW3EjgCTmsH9z6X8QiEjRtNDdvHMYxh7qgBL7NkDboODaXHalqoH/396dx8dV1Y0f/3zvLFmadKEbLW2hUGix7AJF1hZlEQUVDT76KCAqCi2boihLO6yK8ogK6E98fBR3msdHtIiC0AlLS0tDMtOS0pKWJC10S9Om2SaZmXu/vz/SvdkmmZk7y3m/Xn1BZu4959tvTyYn937vOfemqOnTEF0CjAL5a4r6SLkU5idxxTs30TlymNth7C+j8pOB0pkfM7lIQDwuRSIyy+04MpVldfpAznGl88K2r+CJZfTStuXliKpe4HYcgyL3/QKVZ1BOTWU3qtbspDe6SMegjGTy0lpQgU3PJL2PNElJfgarsPFv2AVCXXCk26HskVH5yUDpzI+ZXCTAcbY1imAW0erFhg3T2m3bk/InCnoUL5zEqLqdrvQ9QN01F3Z23lYAiPFDFH8qbz1Zln190hst5QYUm2P+fTRIM/JkRu47MxApyc9gebbfgwKdwx9wO5Q9Mio/GcjkxzASUbvkCxm/xfrBsqnmYg+9+xgqnJ28rM+6HUpCglpFUN9B569DA6+7HU6/sqXmAuDViENV3Qa3wzAyj7lykYCamrrDQ6F687RIL9asWVPqypb0HePvwRPLuC3WD9a95Xrd392OY/CsICPXxVHOT1UPoVB98icuykwc/gHWFCCzN7TrR0ryMxSFza10HTbB7TD2yLj8ZJh05sdMLhLQ1eWxgIwqYMokzc0eAUrS3nHb2GMobsqSqnVJf36SZzHTXhyGUkqFnpGKDlSlNKkNBvVcBD9HvvACOD7oysqt1vdIen6GqrhxBV0lGbMBXMblJ8OY/BjGQAWDhd1Lfocz+/HCg2XlbZF7zkAXKBVOG4s1O1a4DOqfqNBd6PyPofPfdTucAcmm2yLvPD+LoCq1y77odihGZjFXLhKwcKF6wuF149yOI1OpqlVTU5febZgnDv8pCIzacENa+x2kysr6jLmEnDC5fwVIF8O2bMPiolR0UVW1YWKSm5wNVCL3/QO57+gkt512KcjP0Bx3yXIkDh0j3CnkPkjG5SfDpDM/ZnKRgGnTNo5X9f7E7Tgy1fLl60piMfllWjttHf9p/O0OEy/fntZ+B2HhQvV4vWT+pmp90hqmvuRDOYwX9Nhkty6iyavZWaglwHiE7LpC1Iek5idZinZ10TVmhtthQIbmJ4OkMz9mcpGAWMzqUuUtt+PIVF7vsDgQSmunkTGjKGrMiuWcy8pQoMrtOIbG+Quj108AInj5brJbF9E3k9bYWL6OoASzfUK3T1LzkyxFTeuJjChyOwzI0PxkEJMfwxiINa+dTlCVta9/w+1QEpaNNRcAGhiJLlCWNlcT1My+WhTUEBW6Fg18PiseQd0jm2ouANYtuYmgKhuWZNgmZoabzJWLBCxdurEoHK47y+04MlVlZaUvFGo4N20dxsb8HMuG6R/Kis3AVFWqquqyc4XOPSTQDNLIsf/sAkbzqh6XzOarq+tmJ60xZSbCX0GvAT0qae26KKn5SZZp5zyGKLQO+77boWRkfjJIOvNjJhcJKCzUUapyi9txZKp4fEQR6B1p67B9/EkU7oikrb8hKi/HsizJvr1FDuG8xpi1xwHtxJmf3Lat5Ox98LJeieClgEeB00BXJKVd1yUpP8nma7OJjEvfLxa9ytD8ZIz05cdMLhIQjXa1iWgWL4KUWqNH06Wqf0lbh53D/ZRsy5rL3WVlqKrkQMGZ8yToKLzx1xGSuiqqiPPHpDTkcAOwlVlX7QQZDWTtZmX7S1p+kq1oVx2R0cVuh5Gx+ckQJj+G0Z93lv+AoCoNL2bn44XZWnOxhwaibC5/avc296e4Hc4hgtpKUH/fXW+xQNHrXf/BN2DZVnMB8KJ+hqDq7id0DMNcuUjEsmW1w8Phus+5HUemqq2tLaiurrs2LZ21TLwWX8ThyI9kx8JIdK8DUl3d8FW340gOfZvDV52B0IyStEutoVDd14bcSPfqoSXE+S9wPgPSlM2ble0vKflJhdd4BlDG4ernY8bmJ0OkMz9mcpEAv7+gRFWucDuOTNXURIGIfDotnbVNLMLTuSwtfSVJeTkiojkyOdX/BY4D/o4kb0EtVevzQ2+EO4FdXCTVYJ0JGh56ZJkhKflJhYDEERoRPuFmGBmbnwyRzvyYyUUCOjtlp4iaRbR64fXuioA8nPKOntfJqFVC+6i7U95XEpWV4TiO5kjBWesTIB5m/vZVlCJe1iuT064z9IJX4UKEf6NYoBMgy3Zx7VMS8pMqBTu34elMycqtA5fB+ckIJj+G0buX9FEWa5fbYQxJttdcAGjgv9HAWSzWjVRoZhTW/ltPJajKYv0gevel3fUWgTFuh5WQbKy5AFgT+i1BRwkGC90OxXCfuXKRgKqq2rHV1Q0PuR1HpgqHtwwLhxseTXlHvuhVeDTrVkpVVSsUavh/bseRNBL4ChJYhvAb4AyCOuQfKtXV9UNbPt7HnQitXChvgvUFoAUJZPZiXwkYcn5SafjGb4DAxJIfuhVCRucnA6QzP2ZykZACn4hOdTuKTBWJtHpUdVpKOwkGC3F8ExmzcnNK+0mB8nIEkrvoVIZ4cPd/7xp6UzLU/FyM8mL3/1rnAiuHGlFmGXJ+Umfi5dvxRpSOcempu+pRBucnI6QvP2ZykYB16yZvFYmbRbR6MWvWtDafT1P7NMThw38OAuz8Skr7SYGrrhI7Huc/3Y4j6Wbf68XmDWDI/yaqMviC18V6AcpwonsX9poEsmioMWWSIeUnHYqadtIxerxb3Wd8flxm8mMYvVmxuYWlLXG3wxiyXKi5ANDA39BAA4v1AoKq/FtPdS2WoC4mqNu649pTb3H7ONfiGaxsrbkAWF31R1N3YYC5cpGQqqoNE0Oh+hxYYTE1li2rHR4K1af2N8WOMaWUbF2b0j5SZOFC9YRC9YvdjiO5nGeBycy5902gGR9D2l+iurrh5SGcfi4WT3f/7556i0e2DSWeTDPE/KTeyPdvdrPuIuPz47J05sdMLhLg8UTjoDn1YZVMpaUjHFW2pKyD2iU34HihcOutKesjxUTIulqRvlm/BlVwvobDb4ALh1LYKaKbBnViUL8CeGnZu6DX2SCrBhtHphp0ftLF5bqLjM+Py0x+DKMn1XXv8Uqn43YYSZErt0UAdEEtOr+KSi0mqHFe1B+kPYbFuobFuu+KlgZK0Lsmpz2OZMjm2yIAle9tZ0mb7XYYhrvMlYsEVFZW+sLhevO0SC8WLlTPm29uTN3TIm3jJ1KytTFl7aeYqkootD4Hq9nlr2CdwOnSgfAynsEXdobD705P+KTndTLCdDzse0xcAm3IgxsHG0emGlR+0m3Y1kVEh1nUPjc83V1nRX5clM78mMlFAixr3FhVzDoXvZgyZd0wj8dOzToXda+dhV0kFG96LCXtp0F5ORZ4cmedi73aHgH1oXdfSRe3AKMGu2Kn43ieTPgkH48gdHCBPDWYPrPJoPKTbs76mwCIT/hx2rvOhvy4KJ35MZOLBHi9GlHV5W7HkakcpzAGuiQljbeM+yUShxkfeiAl7adBWRkqIrlXcCaPbAPZCp65XCJvobyDzaAK+kScisRP4grgL3u/1ntuR+8+ZjD9Z7pB5SfdZl7Vhr/doX1s2vdhyor8uMjkxzAOtqQlzhubW9wOI2lyqeYCQBc8hS7orhMI6qUEVXlJz055v6/obVSowzLtXltBy/zofAed/6WU950q2V5zARCqe4/XIrlRH2UMirlykYCamm0l4fAGsytqL2prawvC4YbPJL3htS8dQbTUw4hNf05622mkqhIO1+XoIjbyMFCMBs5ljvwLeB+LnyXaSnV1fWK7NtrcCSznLNna/cLMq7s/1t7+Q6J9Z4OE8+OWwm2/IVYoNLx4dDq7zZr8uCSd+TGTiwR0dXUOV3Vy9IfD0DU1UaCq1yS94dj43yEKxy26Meltp1F5OZaqpHYFU7dIYDXQAtwMgMVdwMmJL6olXxvwod11HWOIsf+4uAp0K1IeTazfbJFAftw0/Z8BRKFtwn+lt+MsyY9r0pcfM7lIQEFBYYuIZRbR6sXo0XSJpKCorm3iORQ1dSGBrF6Zs6wMR0RzeGMlqQA+ArC7uHILHn6XWBv6i4Efyg+AWi6S6v1ePAN4LbE+s0kC+XGTBOKgG9j6gYnp7ThL8uMakx/D6Fb73HCCjlKz8m9uh5JUuVZzAaDfnbV7i/MPABDUTxJU5UWdk/S+XtKLd2+tftm+/m8ft7v/i5PeXzrlQs0FQFB/ToV2uB2G4Q5z5SIBK1c2jKqursva1SFTbenSjUWhUN13ktropg/fCKIUNyX/dkuaqaoVDjcscDuOlJHvLQdpB6d7DMyRZxDW4+U3A20iFKq7t/+jAOFXCO9woTy378VhNwFxJPBCImFnkwHnJxNEeQKHIl7Uk9LVZVblxwXpzI+ZXCQgHpciEZnldhyZyrI6fSDnJLVR2/8FYC1T5zQntV0XlJcjqnqB23Gk2GtgfXS/rz+HMpmg3j6Qk1Wt2f0eVKFfBCbhcPVB71wBWjvQQLPRgPKTKS6Rt7CcKKM2/ShdXWZVflyQzvyYyUUCHGdbowh3uh1HptqwYVq7bXtuS1qDAfUCxwM5UflfVoYD9tfdjiO1Yg+B8+reL2fLCiyeQ3mQhVrS39mWZV/f5wHdY+JxhBVcKAetOaPHg/XsoMLOEv3mJ9MMa4zSVZK2CXXW5SfNTH4MA2DFlgcIqkOlFrsdStLlYs1Fb7r3HOkkqK8Mua3F+kcqNMYrOuGA1zVw7u4t1rN/ef5cqbkAeCv8dyrMFuz5yFy5SEA4vG5cKFT3E7fjyFQ1NdtKqqvrk/c0hO35JoW7YpwuOVEUtnChesLh+py4CpOQ06UDm6+gnMfLOrevQ0Oh+t6fxlqsH8TiP4CHOF8O3l32RpAW5JG6JEScsfrMTybybb8BFZhQmpptAQ6SdflJs3Tmx0wuEmDbfi/IOLfjyFStrbssEQ5PSmM1C0voHF3I8A05tVy2KhP6PyoHaMCLXr/vitNH5PcIi1B+zKva6+ZtqtLzo4sLtQSLxSj1zJYeimL1w6DLhh54Zus1P5lq+offx99u0zbhs+noLuvyk2YmP4bxVvjvBB2lLjjS7VBSItdvi+j8beiCA9c8UbUI6iaC2soiHZNQexW6iqBGeF4PndzrbYftfgQ1+avDuiGXbosAhNet59WoWQo8z5grFwnovqy9zly56IWqWjU1dcm5ctE26RKKm7ty4SmR/VVW1ufHlQusFcDHD3hJxKGAExAcSljd0wSjqmrDob9ZBfVVlJkoH+cS2XZoX6U3gdoQ+L+khZ+hesxPpitquoe4T1iz+BOp7ior85NG6cyPmVwkYNq0jeNVvabmohfLl68ricVk6DUXmxaNITLKT+l7/0pCWBlj4UL1eL258eTLAHwPOAwNHLjGwdmygw5OQyiglAYq9Iz93xbRffeEgzqSCl2FcjZwJRfKSz13JZ8Bay1Czv92fEB+ssVxs/6IFYPOSd9PdVdZmZ80Smd+zOQiIV0xVcnpgrGhKCoqtUVk3ZAb2nnMXxBA13xh6FFljrIyFOQdt+NICwm8BtoKTuCQ9y6T9XQwGWUTynIq9CWW6ozuN/UdntPhvKg/QNiKcgwWlzJHnum9M3sB8K2U/D0yjmbn+BnW1EL74cemvqMszU/amPwY+WzJrjhvbMude849yfWaCwAN/BkNtPV5zCt6G0FtZbHq7sdVI1SoQ4XGWKz/IKj59whjrtVcAKwJ/ZagKjXB5Nw2NTKeuXKRgKVLNxaFw3VnuR1HpqqsrPSFQg3nDqmRuuApxIZ7KG34dZLCyhiqKlVVdbm+Qud+4neBDkPvvrTXQ86XR5kjpTicjPKj6Z7oX4BruIACLpSPMUc60xdv5quurpvtdgyDsnnn9YgCo1P6fZ21+UmTdObHTC4SUFioo1TlFrfjyFTx+Igi0DuG1EjLpD+BDcefMS9JYWWM8nIsy+rpMcocJQ+sB9kK3v73m/mIrORCufPPpVsmM1t+h8jA6if0vjyarAFY2bl3xpw5nRQ2R2mbODu1HWVpftImffkxk4sERKNdbSL6d7fjyFSjR9Olqn8ZUiMtR0ynZEtTkkLKKGVlqKrkWcGZ82fgbHRgnzUizh8H3LTe80GwK/buwpoHEspPpindsozIqEI04E1VF1mdnzQw+THyU+2SLxBUZe3yr7gdSsrlQ80FgAZGovMddP5NyW97wdPo/Jakt+u2XKy5AFj70hEEVVlT9f/cDsVIPXPlIgHLltUOD4frPud2HJmqtra2oLq67tpBN7DryJ/gjSjTZ/138qLKHKpqVVc3fNXtONJKAs1gvQ0yoNtcoVDd1wbeuH4YeG2QkWWlxPKTYaZ/+H0K2m1aJ6TsMzSr85MG6cyPmVwkwO8vKFGVK9yOI1M1NVEgIp8e1MmqFm2HH8bw92qSHFbGKC9HRDQPJ6fOj0GORR8c39+RqtbnB9Sk3n0MyGiwfjzk8LLIgPOTqazOZ2k/PGVPAGV9flIsnfkxk4sEdHbKThE1i2j1wuvdFQF5eFAnr1n5e/CA9/1PJTmsjFFWhuM4mn8FZ3LfL0FjELuv/4OdARa8eu8CiSCBF4YWXLYZaH4yVHT0DSh+FmuKVuvM8vyknMmPkW+CTi2vdm5wO4y0yZeaiz10/rPo/OQt5a4LGtEF/05ae5kkV2su9qjQzQS1wu0wjNQyVy4SUFVVO7a6uuEht+PIVOHwlmHhcEPiWys/r5NBpmEX3JWCsDKGqlqhUEOeFrPFvwMyAp3/sb6Oqq6u73/5eL19KjAG7P9KVnTZYkD5yXQe+zlwhrYeTi9yIj8plM78mMlFQgp8IjrV7SgyVSTS6lHVaQmf6OOHQCez5XfJjypzlJcj0Pt24zlNHnoL5A7oWNHPgQPIz7C7gU7kgZzae2ZgBpKfDDd22c/B8rC68v7kN54D+Ump9OXHTC4SsG7d5K0icbOIVi9mzZrW5vNp4k9DeJxP443m/A+Kq64SOx7nP92OwzUS+AHySA+7mu6jKgMpeL0CZEmSosoqA8xPZptxbiX+doeOiUl/PDkn8pNCJj9G/lgd+m+CqryzeJbboaRVvtVcJIt+dwa6QNE7L3I7lJTJ9ZoLgJVrQlTENZULahnuMlcuElBVtWFiKFSfZyssDtyyZbXDQ6H6RQmdtOuoqynaEeW4C5enKKyMsXChekKh+sVux+EqDZSggbt7e7u6uuHlvhvw3w/SijyUm8Wc/eg/P1nC13gV6oG3P5nUGqScyU+KpDM/ZnKRAI8nGgft87JuPistHeGosmXAJ9QuvYTOET5G1D2WwrAyigib3Y7BXW1jQe9H7/lCT++K6Ka+z5dLgZy/hdab/vOTJY4/7x0KdsVpOyKp6y7kTH5SxOTHyA9VGxt5pXNgG1Tlmny+LaILatH5axI/b/6c7lsiOb6XSD7cFgGoWfkCFY5SFxzpdihG8pkrFwmorKz0hcP15mmRXixcqJ4339w4sKdF6oIjaZk4hhF1oRSHlTFUVUKh9aaaHes+kOnot449+J1w+N3pvZ8nAdBGJLA6hcFltL7zk2WKm64CoH3sX5PVZE7lJwXSmR8zuUiAZY0bq4pZ56IXU6asG+bx2ANb56JtYgUIjF13cWqjyhzl5VjgydN1LvYjC34HtMCwJw5+y3E8T/Z+YuwWsK5NXWCZr+/8ZJmpc5op2tbOriPPS1aTOZWfFEhnfszkIgFer0ZUNecLDwfLcQpjoAN7RLB56kkM37iNiZdvT3FYGaOsDBURU3AGgPwCuBANlBzwqjgVvZ/yUAgJPJfiwDJan/nJRiPqvk+sxEP9y5clo7mcy0+SmfwYuW1N6GmCqqx7+Wy3Q3FNPtdcAGjAiwaiaOAXboeScfKl5mKPV6IOVfWm0DDHmCsXCaip2VYSDm8wu6L2ora2tiAcbvhMvwc2Tfs0xY0Rpl2wNA1hZQxVlXC4zixiAyCBOOjfQK9G930OVVfXH/r0gN51JBq4Na3xZage85PtRmyoo+WICcloKifzk0TpzI+ZXCSgq6tzuKpjfjj0oqmJAlW9ps+DapcHiA7zMGrdbWkKK2OUl2OpSuIrmOYsuQHED/Pn7/fa1w49zvdT0BQsFZ2NespPlhu19ROoF1ZX/XHojeVgfpIqffkxk4sEFBQUtohYZhGtXoweTZeIPNXnQY3T76KgOcZxZ+fd5fCyMhwRNRsr7SGB7UAQ5Jv7XtQDx4VigV4KkoQfPLlAc+/7Zso5b1HU1EnzMWVDbywH85NUJj9GLlq35CYqVHl7xQK3Q3Fdvtdc7NF9y8NB77m55/cD3+5+P5A/ayHkW80FwDuv309QlaXvnul2KEZymCsXCVi5smFUdXWduffbi6VLNxaFQnXf6fWAxuMfwddqc/wZ96YxrIyhqlY43GAmVvuTBxuAZeAJAIRCdQePjVvAqUQCzWmPLQP1kJ/ccNyH7kG0ha6p9w2lmZzNT5KkMz9mcpGAeFyKRCS/NthKgGV1+kDO6fHNxXoBnaP8jF6Xt+uElJcjqnqB23FknvZrgJFo4FZVa/bel/W+C0AngvdbbkWWaQ7IT86RXwEfoVKLB9tCbudn6NKZHzO5SEBpaVeTZXny9odjfyKRaR2qek+Pbwr/jVDPjNPm9/h+Higrw7EsMT8oDyY/rAWWAveq7l9/Ef8J8B4y36wNstuB+ckx2/gOgkMLjwy2iZzOTxKY/Bi5JaiXElQlqJe6HUrGMDUXB9Lbp6ILXkUDhd1f763F+LrLkaVfPtZc7PH6rtd5OZqf+w3lGHPlIgHh8LpxoVDdT9yOI1PV1Gwrqa6uP/RpCG/X0wjvMEfydjdL6N57JRyu/4PbcWQkeaQOufe8UPhIYjm4AAAgAElEQVTaX3e/4PsZ0I7cb5ZL308oVJ/bT6uNWnUTjk9YHRrUfiM5n58hSmd+zOQiAbbt94KMczuOTNXaussS4fADXlxT9VvsguEcsWxIhVq5QpWkLBaUq1RlInrbYd2PnzqH7D2S71RlotsxpNSMcysp2dpG03GfGMzpOZ+fITL5MXKDBry82uVQuXmX26FkHHNbpHe6IIzO70QDXrdDcUU+3xYBWLvsMoKqrHnzd26HYgyeuXKRgO5HCbcMczuOTKWqUlOzbd9GVCs/X43tE0rWf9jFsDLKmjVrSt2OIZPd2viLCcBJII3dS4Qb+8uL8TP9rOcobuygaUbCS1XnRX6GIJ35MZOLBFRXbzxctfO/3Y4jUy1fvq40Fuvovqe3YckJ7Jx2AqPWr2HGuZUuh5YRFi5UT2dn4d/cjiOTvVEgYZA4MAkNnOt2PJkmEil61u0Y0mLUuq8QLbZYHUro8zZv8jNI6cyPmVwkpCumKnVuR5GpiopKbRFZB8DmY5ZhxZST/nCiy2FljLIyFOQdt+PIWHr7uNdLN40BfgLUgz7tckQZSPNj/Bx39p8Ytq2dHdOvS+zEPMnPoJn8GNns7RU/IqjK2hWPuR1KxjI1F4fS785AA6+hWGjgJHS+gwYecDustMv3mos93gl+hKAqNeHn3A7FMFJq6dKNReFw3Vlux5GpKisrfU9Xrf4IL3cpb2xtczueTKOqUlVV171Cp5lc9Ki6um723i90/u/RQBx9cLx7Ebmgj8nFAfnJB29u3MHLUSUYLBzI4XmXnwSlMz/mtkgCCgt1lKrc4nYcmSoeH1H0FYY9i3qh9J3T3I4n05SXY1mWmL1F+mTtt/eBdS1oO0QXuxZOxrHya++MwnVnoh4YNXnVwE7Is/wkLH35MZOLBIjYHSK85HYcmer8w5q/3doypYBxq57h+PPMvb2DdNdcYArODqaBy9C7LwWwLF2093UJxMFzBcjx6Pyel5XPMwfkJx/MnLOO0etW0nz0NNYuOaO/w/MuPwky+TGyz6ZFY3glqizfZu4VD4S5LdKtu76iGQ2s6P2YBU+j8+Po3cekMTL3mJqLA2nAy6udjvlsyS7mykUCli2rHR4O133O7Tgy0ntnNqDCk4VbzWX/XqiqVV3d8FW348gsgd8DJRC7EiAUqvvaocfc+zmwdoCnu9gzj/WcnxwngTjj3nqYjrHFvLPiV30dmpf5SUA685PX36iJ8vsLSlTlCrfjyDirVlXQPq542Pjww2dqqdlSvBfl5YiImsnpHnrfqcB/AA8iD24EULUOXThJcKDrfJCxsKA8zVFmlB7zkw+mn/5dSrY2s/nUa/rakj1v8zNA6cyPmVwkoLNTdoqo2bhsfy/qHLbPvIDD1r39chv3gDzsdkiZqqwMx3HUFJxB9+0QnOeBjUhgv6tdTs9XvuR7a4DbgSvzcqfUvXrJTz5oHH8kjidOG//s/aA8zs+AmPwY2WCZjieoESo07HYoWSffay40sLD7MdNvHZvYeQv+ii6wd1/1yE2m5qJ3i/XzBFV5SW9yOxSjb+bKRQKWL39vdHV1/V1ux5ERFqqfCGGETkr4EEBl5abiUKj+frdDy1SqaoVC9Y+4HYfrNPBJ0DJw7kJ+WLv/W6FQ/Y/6PFfu/RTIr8Gp7fO4HNVvfnLdhfJHhBfw6I95Z/Gsg9/O+/z0I535MZOLBPh8ToEIJ7gdR0Y4cmcL4owhypmcLh0A8Xi7FzjF5cgyVnk5AuT3+h9612RgIbAMue+QW2iq8sF+25DAV5BAXi7SNqD85LptXI63U2g8c+nBO+ea/PQtnfkxk4sErFs3eatI3CyitWLzLjpGFnDEmzdxsez9DXLWrGltPp+apyF6cdVVYsfj/KfbcbhGA17wvgHaCqt7LPxVlcQKXruXDM+brdkTzk8uukqijFt+MbEii6ovb9v/LZOfvpn8GJmr8r0mgo6ytvJ7boeS1fKx5kLnV6KBKBo4LoltbkcXrM2pCYapuRiYNZU/J6jKqrUht0MxDmWuXCSgqmrDxFCo/k9ux+GaFZubaZt4GBPffJzpp3/34LeXLasdHgrVmxXgerFwoXpCofr8XMpaF5QDp0H8CiTQ6+qt1dUNLyfWsPVxkKnAWjQwoP0nslni+clhM06/gTGrl9B03MnUhMvB5Kc/6cyPmVwkoKDAdoD8+42iZmEJyxojtI8fwcQVP2T6GT1Wao8caSuQl/fCB07zLz+64FcgnwZrHvLAv/o6VERbE2pbAsvA/hBwBDjvooExQwk10yWcn1x34sxzGVHXQONJn+HtqqdMfvpm8mNkjg1LTuC1NpuKuLL29W+4HU7OyJfbIvrg+N23Qr6d2n6+OwMNtKDz29A7s7vo2twWSVx1wyaCjvJ21VNuh2J0M1cuElBZWekLh+unuh1H2qx5/W7qzlyFeoWJr17E9A/1+RjTwoXqefPNjdPSFV62UVUJhdYnr94gG8hdW4HDkMAPBnJ4OPzu9MH18701sOsosJrAH0Ln52Rh8aDzk+tOPXIiIzZuZsupV1Oz8gW3w8lU6Rw/ZnKRAMsaN1aVh9yOIy1WvrOaLWfdT1FzB8f8exzHzXmxv1OmTFk3zOOxH01HeNmovBwLPP/P7ThSTq8vRsv8e79O4LFRx/E8Oeh+5dEdEJgKznMgT6Lzn82pQk+GmJ9cd9qREyeOWt9B44kXEaqrdzucTJTO8WMmFwnwejWiqsvdjiOl1r3ySZa0xGmadjxj3l7OmWOHMfHy7QM51XEKY6BLUh1itiorQ0UktwvO9J4PwsT3YeZfB3O6iFMxpP4FB7nvCnBuALkEtBGd/+EhtZlBhpyfHPccnkcYF36GnUceybIdXbz9an5dKeyHGT9G+i1UPys2r6DCUZa02bz72lVuh5TTcrHmQud/v3tp7kA9eucEt8NBHzgCXfA2ukDRBf9GAyPdDmlATM3F0NW+cQOvRh0q4sqqVQO6JWcYrqms3FQcDjfkzG9Be1XoPVRoB0Enzlurlw22mZqaGn84XHdpMkPLJd01Fw0fB3JrcqH3fBBdsBGd76CBXwylqXC44fJkhbWXzr8JXRBBF8RSXliaDH1MLlKSnxxyQH42LRrDis3NBFV5WZfxvI5zMbSMkM7xY26LJMCy4iNV9Stux5EUwWAhq2peo8KOAPeiVICM4YQPnDXYJltb/YWqMjd5QeaW7poLzZ0nbvTOCeiCl8Gq7H4hfhoS+NpQmnQcbk9GaAeQ+x6D1SNA/wTOzqS3n0YpyU8OOSA/Ey/fzhkTRiJchcNMCtjEa63/R10wO65gpUA6x09OFTulWkFBYUs83pndi2jVv3wZO478H1omjafJgqLGBraNO4fL5f2hNj16NF0dHWIeBetFWRnOypX6S7fjGDINfAB4HJzZQDvoPOS+J5LU+JCufPRKyqPA1Qd2FfgA8DPougP5XpbUUqUoPzmjh/zMlnJU/0KQnxIfdiMN53+K6nfr8DdczMw561wI0kXpGz+Sro6S6dvXXVfabhd9VESivnbf84+WPxoZ6DEDOTfnvPvS+bRN+jktk2YQK7bwRpXShrUUbfwI0z885EmFMQhBXYByDBfK1f0fnAE04AX7VpAbu1fElJ3Aj5DAA26HNmgauBj0D8CY7r+P8xxYP0ACK12NK6gnICxntgxzNY5ctGnRGLZ9YCm7phyLeqC4qYPS+l9w/Bm5c0UxQ2TdlYvrr7/e1xH1vQrUAttixV1zgYsGcsxAzu3LypUNo2zbuebUU6f+OGl/oVSoCR6OjPoxkdEX0z52JA0FgsShpHEXY2seZvqZKdkXZOnSjUXFxfFbTjll6vdT0b7bVNULTO+A/4jF+VBrnBHDvWwu8BK0YEncZkpEmdlpUzzcx0aPw5tFXlaJSNvu862VKzfcc/LJR97bTz+jO20us4WPttlM9QtdBRYriy3+ArwhIumbEGtgZPcTQDoDPAKsBMqQwP+mortQqO7eU06ZuiAVbR9CAi8AY7ufcPEEwPoE6H+iCzqAEMjfoO03yCPb+mlpSFS1oA2mic0ZHTbTNnZxxAs78d9k66M7uvAO97HF56WqGJaFw/W37p8fVR0ZgUsdh8vabaaJQ7zIR43P4pkCWLJn7A0hNgsY32ozy1ZObLMZPsrH+x6LNwshJCIZteJjv+On+8m349CAl9Wf+jvNUy9iy+m3URG/jeLtrQzf8k8Kdn6NqXOa0xd1+qTz+yvrJhf+mP+ziDY88ZsnygDmXTu3et4X5019/HeP1/V3DDHO6e/cvsTjUmRZMisVf69Be14nU9x1BcPf+wadI46ga4SfbT5BFHwdNiWb32PYlh/3twBWMlhWpw9856S6H7d0wVFtcX6yvoM5b7djbY/DpAL4QAmXHFXImpVtTFzTQWmbjU4uxJ5RzKrpXh5W1UUiYpeXI8cdpz3uBrqHqlpxh6/XR/nmug5GvhtBCi04tpjzjy3mwkl+vgEkf5EgLfPDzNngXAbevyLzux+ZlUAzOr8V9B7Y+mPkyY6k971/GGrNTmX7PZL73wS6C930zlPAfzNwIej3YNjD6PwIsAGsENhLIf5C96JdQ6eqEoNTtnbyjXUdXPJuhMIZJXguHoX3mUZufr+L+OEF6MxiWk8YxkMinjnAgt3nWl0OX36/kzs3RhlV24FEFaYWce5xRVxyZBF3qOpfRMQZbHzt7Yxt9/H1d7v4+tttjNwZx5lSiHNcMetnFPJ9VX1aROxk5CIZBjx+JBCHwGUA1AVPoW3iU7RMmMmWk65C5Spe61AKm1soag5T2PQUx5z3P6mLOn3S+f2VdZMLlJkg4X1fy9vidT4I1PV3jKrV/7l9KC3taopECtOziNamRWPoGHEu0eIPor4ZOP6jiRWNJ1Y4knhRIbGSKI5VgGBhFygtk8DX2sWIDbX4mheytfVBzpnTmZZYd4tEpnUUFNTfk84+08mJcVlTjAu/vxH5WyM4wAgvfHE8/nuO4sSfb4I/bUUcYGIBev0EPnjrZK4f4WEF8H5ZGc6qVfKtfrqZFnG44Z/bGfX4JqjbfY3irBFI4ChmjvDwRQYzuejec2Ma2B8Az9HAccCRoBNBRoMWgQLSCfHNwL71OOS+QRf5JhymyjfT1VeP5KEQcN3er/W+C8ApA2aBXgRWGfgtdP4fkPu+sO+4wOPd/+OsB6cB/HXg1CGB/n4DHt7pcOXSXXz8vzZStCOGvHwq3NcAf9iCFVP8FnDlWPy/mE5g5OjhX97v3HExuHl1B4c9vBGW7eoek8cUIbccwdQvTeCrfg+vAFsHnY8CTtnSyS0PNVD6j+1YDnCYD/3S4Rx/15Hc7IfXgA2Dbj/JBjV+ps4JAScD3fsoWcd8n8joK4mMGkfbuPNxPOcTdH4F0gZsB96jaEcnJZs9eDtWYcWXoZFXsuEWczq/v7JwcqHjRXhtz5ciuhk4fEDHDODcyspNxX5/7PB4PNp62mnHNq5c2TAKGOX3RxqPPfbYVs/aN56xVq0eq92/dKiIWt1diiMWQrzAj6OoiAqg6vXgeAVBrWhxs6dzeGsciatQhK/tCNRroQJqCWrR/Udg7X5BiYIVB09M8UYchjXHCuJtVZMi4/7VGfMuen+OhMdGv/+4WhRu93S0eLFKR00reCIafTC+y9fVXuR4fSW2rzhixbvaPLHOEqegsMi2Cpo90faYZcevbjnhz7c3zNq+Zs2UhjvLbvbuik38mW2pvcPT2eZzLO9Iu2BYp+XEWj1dHcWOt2CY7Stss6KRiMeOjrALiv2O5Wv2dLXNsRbY97173q/D4fqpJ598VN309ocn7vA590ctJ77L03scLb54exex+Ci7sMTriKfJ09niWGKvXPWln0Wj8fjppx+z4eiuH53YKl237omjyPH5S2xvUZsnHolYsQPiiFmOfVisoNSDZTX6Irssx2oL1XzpN/G4dJ522pRNkyLfm93l4Yt747B9hUWOd28cI+yCYX7H8jZ5ulody3HGxopG2DjOG573ZkdaJ8kzjd0/hgF2xWFRE3zhcCTqdH+4A2zqQv61U71njd11xj8LX/8VOn+1xwnI6BmFw0fFH7J3vrPyBE/bOG/1yoajIxHPrlmzJjWNjX7/lu/pK9deGf/QuBd2+nh3v5sfr++CyhYoLtnxSXTB84KM9KvH76ASk7i/yPFVLK+5+hHbdnaceurUZp/e90ZcnVNU1ANY+yK2HCBmQbsH2RFDV/sca80HOsa8XdZ48j/vPvqchpqajYfZK798tMdTtG3mzHFtlZX1E/x+KYpGGzeefvrpsXC4fqptO85ppx3dUFNT47ftkkkej9Mxc+bULcuW1Q4vLvaP2RNHVVXtWK/XX9rWZm0+++zJkVWr1k1W9flOPHFKHSCrVm04StUTPfnkSe9VVm4q9npjOyorN405/fSJ2/f/3psxY0brwXFUV9cdBXDqqVPrD45jzZo1pdFo0Vhg50knHbnz4DjC4fcmidj+E0+cUg+wfxxLl24sKilxJsTj0dbT5NiXV65sWLl/HJ9t//0ZE9pGeL9aU+OfOXNmtLq67qgz9beXxcQZC1YRiAd2/zKvC6B7vmmDxgTigjgK7YrjnKlP6mPxss1Lmkf5wm3IZ8ZCaxx+twXs3f9kDvC/jcitR9rFFRPDd/nt+z8TtezYl+2/H/Ud+6MTqtt8LN21b6ysj8DiZrh4tM542P/Mk+j89f19Buz/vYclOjpWMOLJhvMfisNJtREKnt2OtWcE7Yghz+5Qz8cObz/uH94lj42IP7j5wO+9wuEeRHZ/71ljtMj3r5Wfe/C006ZsqqnZVvKdcc/ODo56/7Kevvf2xXHg994OX1erD8szvmtY9J+1n37kxBOP3lpZuX7ErccuvuzNki3n7PkMuMT5g8+ngbYYh3wGWKPtgtK4pfZOT2dbAT7vhM7ipqdXfvbxWbMmNS1f/t7or53w90+tLVxzcsR6KzrCLli09zOga8RhBdtPPNnZOcUf6xxVQrzoRKIlJTTN8OB45gA3AxDU7n/qPX8sR7Fi3f+CnpiCKJ6oIypxsf0tjhWNiIiIp2ukiu1XX1dMUMT2RFV9baqoR9Wr3liJ4ngUUcvXaSO2OoItWHhtbye2vzmGxi3FI77OsY7l+BRVQcR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       "                        this.mouseover(fn2, scope);\n",
       "                    } else {\n",
       "                        this.mouseout(fn2, scope);\n",
       "                    }\n",
       "                }\n",
       "                return this;\n",
       "            };\n",
       "        })(events[i]);\n",
       "    }\n",
       "\n",
       "\n",
       "    Element.prototype.mousewheel = function (fn, scope) {\n",
       "        if (Snap.is(fn, \"function\")) {\n",
       "            var el = this;\n",
       "            var fn2 = function (event) {\n",
       "                fn.apply(el, [event]);\n",
       "            };\n",
       "        }\n",
       "\n",
       "        this.node.addEventListener(\n",
       "            /Firefox/i.test(navigator.userAgent) ? \"DOMMouseScroll\" : \"mousewheel\",\n",
       "            fn2);\n",
       "\n",
       "        return this;\n",
       "    };\n",
       "\n",
       "\n",
       "    // Snap's attr function can be too slow for things like panning/zooming.\n",
       "    // This is a function to directly update element attributes without going\n",
       "    // through eve.\n",
       "    Element.prototype.attribute = function(key, val) {\n",
       "        if (val === undefined) {\n",
       "            return this.node.getAttribute(key);\n",
       "        } else {\n",
       "            this.node.setAttribute(key, val);\n",
       "            return this;\n",
       "        }\n",
       "    };\n",
       "\n",
       "    Element.prototype.init_gadfly = function() {\n",
       "        this.mouseenter(Gadfly.plot_mouseover)\n",
       "            .mouseleave(Gadfly.plot_mouseout)\n",
       "            .dblclick(Gadfly.plot_dblclick)\n",
       "            .mousewheel(Gadfly.guide_background_scroll)\n",
       "            .drag(Gadfly.guide_background_drag_onmove,\n",
       "                  Gadfly.guide_background_drag_onstart,\n",
       "                  Gadfly.guide_background_drag_onend);\n",
       "        this.mouseenter(function (event) {\n",
       "            init_pan_zoom(this.plotroot());\n",
       "        });\n",
       "        return this;\n",
       "    };\n",
       "});\n",
       "\n",
       "\n",
       "// When the plot is moused over, emphasize the grid lines.\n",
       "Gadfly.plot_mouseover = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    var keyboard_zoom = function(event) {\n",
       "        if (event.which == 187) { // plus\n",
       "            increase_zoom_by_position(root, 0.1, true);\n",
       "        } else if (event.which == 189) { // minus\n",
       "            increase_zoom_by_position(root, -0.1, true);\n",
       "        }\n",
       "    };\n",
       "    root.data(\"keyboard_zoom\", keyboard_zoom);\n",
       "    window.addEventListener(\"keyup\", keyboard_zoom);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    xgridlines.data(\"unfocused_strokedash\",\n",
       "                    xgridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "    ygridlines.data(\"unfocused_strokedash\",\n",
       "                    ygridlines.attribute(\"stroke-dasharray\").replace(/(\\d)(,|$)/g, \"$1mm$2\"));\n",
       "\n",
       "    // emphasize grid lines\n",
       "    var destcolor = root.data(\"focused_xgrid_color\");\n",
       "    xgridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"focused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", \"none\")\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // reveal zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 1.0}, 250);\n",
       "};\n",
       "\n",
       "// Reset pan and zoom on double click\n",
       "Gadfly.plot_dblclick = function(event) {\n",
       "  set_plot_pan_zoom(this.plotroot(), 0.0, 0.0, 1.0);\n",
       "};\n",
       "\n",
       "// Unemphasize grid lines on mouse out.\n",
       "Gadfly.plot_mouseout = function(event) {\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    window.removeEventListener(\"keyup\", root.data(\"keyboard_zoom\"));\n",
       "    root.data(\"keyboard_zoom\", undefined);\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\"),\n",
       "        ygridlines = root.select(\".ygridlines\");\n",
       "\n",
       "    var destcolor = root.data(\"unfocused_xgrid_color\");\n",
       "\n",
       "    xgridlines.attribute(\"stroke-dasharray\", xgridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    destcolor = root.data(\"unfocused_ygrid_color\");\n",
       "    ygridlines.attribute(\"stroke-dasharray\", ygridlines.data(\"unfocused_strokedash\"))\n",
       "              .selectAll(\"path\")\n",
       "              .animate({stroke: destcolor}, 250);\n",
       "\n",
       "    // hide zoom slider\n",
       "    root.select(\".zoomslider\")\n",
       "        .animate({opacity: 0.0}, 250);\n",
       "};\n",
       "\n",
       "\n",
       "var set_geometry_transform = function(root, tx, ty, scale) {\n",
       "    var xscalable = root.hasClass(\"xscalable\"),\n",
       "        yscalable = root.hasClass(\"yscalable\");\n",
       "\n",
       "    var old_scale = root.data(\"scale\");\n",
       "\n",
       "    var xscale = xscalable ? scale : 1.0,\n",
       "        yscale = yscalable ? scale : 1.0;\n",
       "\n",
       "    tx = xscalable ? tx : 0.0;\n",
       "    ty = yscalable ? ty : 0.0;\n",
       "\n",
       "    var t = new Snap.Matrix().translate(tx, ty).scale(xscale, yscale);\n",
       "\n",
       "    root.selectAll(\".geometry, image\")\n",
       "        .forEach(function (element, i) {\n",
       "            element.transform(t);\n",
       "        });\n",
       "\n",
       "    bounds = root.plotbounds();\n",
       "\n",
       "    if (yscalable) {\n",
       "        var xfixed_t = new Snap.Matrix().translate(0, ty).scale(1.0, yscale);\n",
       "        root.selectAll(\".xfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(xfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".ylabels\")\n",
       "            .transform(xfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1, 1/scale, cx, cy).add(st);\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var y = cy * scale + ty;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.y0 <= y && y <= bounds.y1 ? \"visible\" : \"hidden\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (xscalable) {\n",
       "        var yfixed_t = new Snap.Matrix().translate(tx, 0).scale(xscale, 1.0);\n",
       "        var xtrans = new Snap.Matrix().translate(tx, 0);\n",
       "        root.selectAll(\".yfixed\")\n",
       "            .forEach(function (element, i) {\n",
       "                element.transform(yfixed_t);\n",
       "            });\n",
       "\n",
       "        root.select(\".xlabels\")\n",
       "            .transform(yfixed_t)\n",
       "            .selectAll(\"text\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var cx = element.asPX(\"x\"),\n",
       "                        cy = element.asPX(\"y\");\n",
       "                    var st = element.data(\"static_transform\");\n",
       "                    unscale_t = new Snap.Matrix();\n",
       "                    unscale_t.scale(1/scale, 1, cx, cy).add(st);\n",
       "\n",
       "                    element.transform(unscale_t);\n",
       "\n",
       "                    var x = cx * scale + tx;\n",
       "                    element.attr(\"visibility\",\n",
       "                        bounds.x0 <= x && x <= bounds.x1 ? \"visible\" : \"hidden\");\n",
       "                    }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // we must unscale anything that is scale invariance: widths, raiduses, etc.\n",
       "    var size_attribs = [\"font-size\"];\n",
       "    var unscaled_selection = \".geometry, .geometry *\";\n",
       "    if (xscalable) {\n",
       "        size_attribs.push(\"rx\");\n",
       "        unscaled_selection += \", .xgridlines\";\n",
       "    }\n",
       "    if (yscalable) {\n",
       "        size_attribs.push(\"ry\");\n",
       "        unscaled_selection += \", .ygridlines\";\n",
       "    }\n",
       "\n",
       "    root.selectAll(unscaled_selection)\n",
       "        .forEach(function (element, i) {\n",
       "            // circle need special help\n",
       "            if (element.node.nodeName == \"circle\") {\n",
       "                var cx = element.attribute(\"cx\"),\n",
       "                    cy = element.attribute(\"cy\");\n",
       "                unscale_t = new Snap.Matrix().scale(1/xscale, 1/yscale,\n",
       "                                                        cx, cy);\n",
       "                element.transform(unscale_t);\n",
       "                return;\n",
       "            }\n",
       "\n",
       "            for (i in size_attribs) {\n",
       "                var key = size_attribs[i];\n",
       "                var val = parseFloat(element.attribute(key));\n",
       "                if (val !== undefined && val != 0 && !isNaN(val)) {\n",
       "                    element.attribute(key, val * old_scale / scale);\n",
       "                }\n",
       "            }\n",
       "        });\n",
       "};\n",
       "\n",
       "\n",
       "// Find the most appropriate tick scale and update label visibility.\n",
       "var update_tickscale = function(root, scale, axis) {\n",
       "    if (!root.hasClass(axis + \"scalable\")) return;\n",
       "\n",
       "    var tickscales = root.data(axis + \"tickscales\");\n",
       "    var best_tickscale = 1.0;\n",
       "    var best_tickscale_dist = Infinity;\n",
       "    for (tickscale in tickscales) {\n",
       "        var dist = Math.abs(Math.log(tickscale) - Math.log(scale));\n",
       "        if (dist < best_tickscale_dist) {\n",
       "            best_tickscale_dist = dist;\n",
       "            best_tickscale = tickscale;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    if (best_tickscale != root.data(axis + \"tickscale\")) {\n",
       "        root.data(axis + \"tickscale\", best_tickscale);\n",
       "        var mark_inscale_gridlines = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        var mark_inscale_labels = function (element, i) {\n",
       "            var inscale = element.attr(\"gadfly:scale\") == best_tickscale;\n",
       "            element.attribute(\"gadfly:inscale\", inscale);\n",
       "            element.attr(\"visibility\", inscale ? \"visible\" : \"hidden\");\n",
       "        };\n",
       "\n",
       "        root.select(\".\" + axis + \"gridlines\").selectAll(\"path\").forEach(mark_inscale_gridlines);\n",
       "        root.select(\".\" + axis + \"labels\").selectAll(\"text\").forEach(mark_inscale_labels);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "var set_plot_pan_zoom = function(root, tx, ty, scale) {\n",
       "    var old_scale = root.data(\"scale\");\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    // compute the viewport derived from tx, ty, and scale\n",
       "    var x_min = -width * scale - (scale * width - width),\n",
       "        x_max = width * scale,\n",
       "        y_min = -height * scale - (scale * height - height),\n",
       "        y_max = height * scale;\n",
       "\n",
       "    var x0 = bounds.x0 - scale * bounds.x0,\n",
       "        y0 = bounds.y0 - scale * bounds.y0;\n",
       "\n",
       "    var tx = Math.max(Math.min(tx - x0, x_max), x_min),\n",
       "        ty = Math.max(Math.min(ty - y0, y_max), y_min);\n",
       "\n",
       "    tx += x0;\n",
       "    ty += y0;\n",
       "\n",
       "    // when the scale change, we may need to alter which set of\n",
       "    // ticks is being displayed\n",
       "    if (scale != old_scale) {\n",
       "        update_tickscale(root, scale, \"x\");\n",
       "        update_tickscale(root, scale, \"y\");\n",
       "    }\n",
       "\n",
       "    set_geometry_transform(root, tx, ty, scale);\n",
       "\n",
       "    root.data(\"scale\", scale);\n",
       "    root.data(\"tx\", tx);\n",
       "    root.data(\"ty\", ty);\n",
       "};\n",
       "\n",
       "\n",
       "var scale_centered_translation = function(root, scale) {\n",
       "    var bounds = root.plotbounds();\n",
       "\n",
       "    var width = bounds.x1 - bounds.x0,\n",
       "        height = bounds.y1 - bounds.y0;\n",
       "\n",
       "    var tx0 = root.data(\"tx\"),\n",
       "        ty0 = root.data(\"ty\");\n",
       "\n",
       "    var scale0 = root.data(\"scale\");\n",
       "\n",
       "    // how off from center the current view is\n",
       "    var xoff = tx0 - (bounds.x0 * (1 - scale0) + (width * (1 - scale0)) / 2),\n",
       "        yoff = ty0 - (bounds.y0 * (1 - scale0) + (height * (1 - scale0)) / 2);\n",
       "\n",
       "    // rescale offsets\n",
       "    xoff = xoff * scale / scale0;\n",
       "    yoff = yoff * scale / scale0;\n",
       "\n",
       "    // adjust for the panel position being scaled\n",
       "    var x_edge_adjust = bounds.x0 * (1 - scale),\n",
       "        y_edge_adjust = bounds.y0 * (1 - scale);\n",
       "\n",
       "    return {\n",
       "        x: xoff + x_edge_adjust + (width - width * scale) / 2,\n",
       "        y: yoff + y_edge_adjust + (height - height * scale) / 2\n",
       "    };\n",
       "};\n",
       "\n",
       "\n",
       "// Initialize data for panning zooming if it isn't already.\n",
       "var init_pan_zoom = function(root) {\n",
       "    if (root.data(\"zoompan-ready\")) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    // The non-scaling-stroke trick. Rather than try to correct for the\n",
       "    // stroke-width when zooming, we force it to a fixed value.\n",
       "    var px_per_mm = root.node.getCTM().a;\n",
       "\n",
       "    // Drag events report deltas in pixels, which we'd like to convert to\n",
       "    // millimeters.\n",
       "    root.data(\"px_per_mm\", px_per_mm);\n",
       "\n",
       "    root.selectAll(\"path\")\n",
       "        .forEach(function (element, i) {\n",
       "        sw = element.asPX(\"stroke-width\") * px_per_mm;\n",
       "        if (sw > 0) {\n",
       "            element.attribute(\"stroke-width\", sw);\n",
       "            element.attribute(\"vector-effect\", \"non-scaling-stroke\");\n",
       "        }\n",
       "    });\n",
       "\n",
       "    // Store ticks labels original tranformation\n",
       "    root.selectAll(\".xlabels > text, .ylabels > text\")\n",
       "        .forEach(function (element, i) {\n",
       "            var lm = element.transform().localMatrix;\n",
       "            element.data(\"static_transform\",\n",
       "                new Snap.Matrix(lm.a, lm.b, lm.c, lm.d, lm.e, lm.f));\n",
       "        });\n",
       "\n",
       "    var xgridlines = root.select(\".xgridlines\");\n",
       "    var ygridlines = root.select(\".ygridlines\");\n",
       "    var xlabels = root.select(\".xlabels\");\n",
       "    var ylabels = root.select(\".ylabels\");\n",
       "\n",
       "    if (root.data(\"tx\") === undefined) root.data(\"tx\", 0);\n",
       "    if (root.data(\"ty\") === undefined) root.data(\"ty\", 0);\n",
       "    if (root.data(\"scale\") === undefined) root.data(\"scale\", 1.0);\n",
       "    if (root.data(\"xtickscales\") === undefined) {\n",
       "\n",
       "        // index all the tick scales that are listed\n",
       "        var xtickscales = {};\n",
       "        var ytickscales = {};\n",
       "        var add_x_tick_scales = function (element, i) {\n",
       "            xtickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "        var add_y_tick_scales = function (element, i) {\n",
       "            ytickscales[element.attribute(\"gadfly:scale\")] = true;\n",
       "        };\n",
       "\n",
       "        if (xgridlines) xgridlines.selectAll(\"path\").forEach(add_x_tick_scales);\n",
       "        if (ygridlines) ygridlines.selectAll(\"path\").forEach(add_y_tick_scales);\n",
       "        if (xlabels) xlabels.selectAll(\"text\").forEach(add_x_tick_scales);\n",
       "        if (ylabels) ylabels.selectAll(\"text\").forEach(add_y_tick_scales);\n",
       "\n",
       "        root.data(\"xtickscales\", xtickscales);\n",
       "        root.data(\"ytickscales\", ytickscales);\n",
       "        root.data(\"xtickscale\", 1.0);\n",
       "    }\n",
       "\n",
       "    var min_scale = 1.0, max_scale = 1.0;\n",
       "    for (scale in xtickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    for (scale in ytickscales) {\n",
       "        min_scale = Math.min(min_scale, scale);\n",
       "        max_scale = Math.max(max_scale, scale);\n",
       "    }\n",
       "    root.data(\"min_scale\", min_scale);\n",
       "    root.data(\"max_scale\", max_scale);\n",
       "\n",
       "    // store the original positions of labels\n",
       "    if (xlabels) {\n",
       "        xlabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"x\", element.asPX(\"x\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    if (ylabels) {\n",
       "        ylabels.selectAll(\"text\")\n",
       "               .forEach(function (element, i) {\n",
       "                   element.data(\"y\", element.asPX(\"y\"));\n",
       "               });\n",
       "    }\n",
       "\n",
       "    // mark grid lines and ticks as in or out of scale.\n",
       "    var mark_inscale = function (element, i) {\n",
       "        element.attribute(\"gadfly:inscale\", element.attribute(\"gadfly:scale\") == 1.0);\n",
       "    };\n",
       "\n",
       "    if (xgridlines) xgridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (ygridlines) ygridlines.selectAll(\"path\").forEach(mark_inscale);\n",
       "    if (xlabels) xlabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "    if (ylabels) ylabels.selectAll(\"text\").forEach(mark_inscale);\n",
       "\n",
       "    // figure out the upper ond lower bounds on panning using the maximum\n",
       "    // and minum grid lines\n",
       "    var bounds = root.plotbounds();\n",
       "    var pan_bounds = {\n",
       "        x0: 0.0,\n",
       "        y0: 0.0,\n",
       "        x1: 0.0,\n",
       "        y1: 0.0\n",
       "    };\n",
       "\n",
       "    if (xgridlines) {\n",
       "        xgridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.x1 - bbox.x < pan_bounds.x0) {\n",
       "                        pan_bounds.x0 = bounds.x1 - bbox.x;\n",
       "                    }\n",
       "                    if (bounds.x0 - bbox.x > pan_bounds.x1) {\n",
       "                        pan_bounds.x1 = bounds.x0 - bbox.x;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    if (ygridlines) {\n",
       "        ygridlines\n",
       "            .selectAll(\"path\")\n",
       "            .forEach(function (element, i) {\n",
       "                if (element.attribute(\"gadfly:inscale\") == \"true\") {\n",
       "                    var bbox = element.node.getBBox();\n",
       "                    if (bounds.y1 - bbox.y < pan_bounds.y0) {\n",
       "                        pan_bounds.y0 = bounds.y1 - bbox.y;\n",
       "                    }\n",
       "                    if (bounds.y0 - bbox.y > pan_bounds.y1) {\n",
       "                        pan_bounds.y1 = bounds.y0 - bbox.y;\n",
       "                    }\n",
       "                    element.attr(\"visibility\", \"visible\");\n",
       "                }\n",
       "            });\n",
       "    }\n",
       "\n",
       "    // nudge these values a little\n",
       "    pan_bounds.x0 -= 5;\n",
       "    pan_bounds.x1 += 5;\n",
       "    pan_bounds.y0 -= 5;\n",
       "    pan_bounds.y1 += 5;\n",
       "    root.data(\"pan_bounds\", pan_bounds);\n",
       "\n",
       "    root.data(\"zoompan-ready\", true)\n",
       "};\n",
       "\n",
       "\n",
       "// drag actions, i.e. zooming and panning\n",
       "var pan_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        root.data(\"dx\", 0);\n",
       "        root.data(\"dy\", 0);\n",
       "        root.data(\"tx0\", root.data(\"tx\"));\n",
       "        root.data(\"ty0\", root.data(\"ty\"));\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        dx /= px_per_mm;\n",
       "        dy /= px_per_mm;\n",
       "\n",
       "        var tx0 = root.data(\"tx\"),\n",
       "            ty0 = root.data(\"ty\");\n",
       "\n",
       "        var dx0 = root.data(\"dx\"),\n",
       "            dy0 = root.data(\"dy\");\n",
       "\n",
       "        root.data(\"dx\", dx);\n",
       "        root.data(\"dy\", dy);\n",
       "\n",
       "        dx = dx - dx0;\n",
       "        dy = dy - dy0;\n",
       "\n",
       "        var tx = tx0 + dx,\n",
       "            ty = ty0 + dy;\n",
       "\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\"));\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        set_plot_pan_zoom(root, root.data(\"tx0\"), root.data(\"ty0\"), root.data(\"scale\"));\n",
       "    }\n",
       "};\n",
       "\n",
       "var zoom_box;\n",
       "var zoom_action = {\n",
       "    start: function(root, x, y, event) {\n",
       "        var bounds = root.plotbounds();\n",
       "        var width = bounds.x1 - bounds.x0,\n",
       "            height = bounds.y1 - bounds.y0;\n",
       "        var ratio = width / height;\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        x = xscalable ? x / px_per_mm : bounds.x0;\n",
       "        y = yscalable ? y / px_per_mm : bounds.y0;\n",
       "        var w = xscalable ? 0 : width;\n",
       "        var h = yscalable ? 0 : height;\n",
       "        zoom_box = root.rect(x, y, w, h).attr({\n",
       "            \"fill\": \"#000\",\n",
       "            \"opacity\": 0.25\n",
       "        });\n",
       "        zoom_box.data(\"ratio\", ratio);\n",
       "    },\n",
       "    update: function(root, dx, dy, x, y, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var px_per_mm = root.data(\"px_per_mm\");\n",
       "        var bounds = root.plotbounds();\n",
       "        if (yscalable) {\n",
       "            y /= px_per_mm;\n",
       "            y = Math.max(bounds.y0, y);\n",
       "            y = Math.min(bounds.y1, y);\n",
       "        } else {\n",
       "            y = bounds.y1;\n",
       "        }\n",
       "        if (xscalable) {\n",
       "            x /= px_per_mm;\n",
       "            x = Math.max(bounds.x0, x);\n",
       "            x = Math.min(bounds.x1, x);\n",
       "        } else {\n",
       "            x = bounds.x1;\n",
       "        }\n",
       "\n",
       "        dx = x - zoom_box.attr(\"x\");\n",
       "        dy = y - zoom_box.attr(\"y\");\n",
       "        if (xscalable && yscalable) {\n",
       "            var ratio = zoom_box.data(\"ratio\");\n",
       "            var width = Math.min(Math.abs(dx), ratio * Math.abs(dy));\n",
       "            var height = Math.min(Math.abs(dy), Math.abs(dx) / ratio);\n",
       "            dx = width * dx / Math.abs(dx);\n",
       "            dy = height * dy / Math.abs(dy);\n",
       "        }\n",
       "        var xoffset = 0,\n",
       "            yoffset = 0;\n",
       "        if (dx < 0) {\n",
       "            xoffset = dx;\n",
       "            dx = -1 * dx;\n",
       "        }\n",
       "        if (dy < 0) {\n",
       "            yoffset = dy;\n",
       "            dy = -1 * dy;\n",
       "        }\n",
       "        if (isNaN(dy)) {\n",
       "            dy = 0.0;\n",
       "        }\n",
       "        if (isNaN(dx)) {\n",
       "            dx = 0.0;\n",
       "        }\n",
       "        zoom_box.transform(\"T\" + xoffset + \",\" + yoffset);\n",
       "        zoom_box.attr(\"width\", dx);\n",
       "        zoom_box.attr(\"height\", dy);\n",
       "    },\n",
       "    end: function(root, event) {\n",
       "        var xscalable = root.hasClass(\"xscalable\"),\n",
       "            yscalable = root.hasClass(\"yscalable\");\n",
       "        var zoom_bounds = zoom_box.getBBox();\n",
       "        if (zoom_bounds.width * zoom_bounds.height <= 0) {\n",
       "            return;\n",
       "        }\n",
       "        var plot_bounds = root.plotbounds();\n",
       "        var zoom_factor = 1.0;\n",
       "        if (yscalable) {\n",
       "            zoom_factor = (plot_bounds.y1 - plot_bounds.y0) / zoom_bounds.height;\n",
       "        } else {\n",
       "            zoom_factor = (plot_bounds.x1 - plot_bounds.x0) / zoom_bounds.width;\n",
       "        }\n",
       "        var tx = (root.data(\"tx\") - zoom_bounds.x) * zoom_factor + plot_bounds.x0,\n",
       "            ty = (root.data(\"ty\") - zoom_bounds.y) * zoom_factor + plot_bounds.y0;\n",
       "        set_plot_pan_zoom(root, tx, ty, root.data(\"scale\") * zoom_factor);\n",
       "        zoom_box.remove();\n",
       "    },\n",
       "    cancel: function(root) {\n",
       "        zoom_box.remove();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onstart = function(x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var scalable = root.hasClass(\"xscalable\") || root.hasClass(\"yscalable\");\n",
       "    var zoomable = !event.altKey && !event.ctrlKey && event.shiftKey && scalable;\n",
       "    var panable = !event.altKey && !event.ctrlKey && !event.shiftKey && scalable;\n",
       "    var drag_action = zoomable ? zoom_action :\n",
       "                      panable  ? pan_action :\n",
       "                                 undefined;\n",
       "    root.data(\"drag_action\", drag_action);\n",
       "    if (drag_action) {\n",
       "        var cancel_drag_action = function(event) {\n",
       "            if (event.which == 27) { // esc key\n",
       "                drag_action.cancel(root);\n",
       "                root.data(\"drag_action\", undefined);\n",
       "            }\n",
       "        };\n",
       "        window.addEventListener(\"keyup\", cancel_drag_action);\n",
       "        root.data(\"cancel_drag_action\", cancel_drag_action);\n",
       "        drag_action.start(root, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.update(root, dx, dy, x, y, event);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_drag_onend = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    window.removeEventListener(\"keyup\", root.data(\"cancel_drag_action\"));\n",
       "    root.data(\"cancel_drag_action\", undefined);\n",
       "    var drag_action = root.data(\"drag_action\");\n",
       "    if (drag_action) {\n",
       "        drag_action.end(root, event);\n",
       "    }\n",
       "    root.data(\"drag_action\", undefined);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.guide_background_scroll = function(event) {\n",
       "    if (event.shiftKey) {\n",
       "        increase_zoom_by_position(this.plotroot(), 0.001 * event.wheelDelta);\n",
       "        event.preventDefault();\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseover = function(event) {\n",
       "    this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_button_mouseout = function(event) {\n",
       "     this.select(\".button_logo\")\n",
       "         .animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomout_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), -0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_zoomin_click = function(event) {\n",
       "    increase_zoom_by_position(this.plotroot(), 0.1, true);\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_track_click = function(event) {\n",
       "    // TODO\n",
       "};\n",
       "\n",
       "\n",
       "// Map slider position x to scale y using the function y = a*exp(b*x)+c.\n",
       "// The constants a, b, and c are solved using the constraint that the function\n",
       "// should go through the points (0; min_scale), (0.5; 1), and (1; max_scale).\n",
       "var scale_from_slider_position = function(position, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return a * Math.exp(b * position) + c;\n",
       "}\n",
       "\n",
       "// inverse of scale_from_slider_position\n",
       "var slider_position_from_scale = function(scale, min_scale, max_scale) {\n",
       "    var a = (1 - 2 * min_scale + min_scale * min_scale) / (min_scale + max_scale - 2),\n",
       "        b = 2 * Math.log((max_scale - 1) / (1 - min_scale)),\n",
       "        c = (min_scale * max_scale - 1) / (min_scale + max_scale - 2);\n",
       "    return 1 / b * Math.log((scale - c) / a);\n",
       "}\n",
       "\n",
       "var increase_zoom_by_position = function(root, delta_position, animate) {\n",
       "    var scale = root.data(\"scale\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\");\n",
       "    var position = slider_position_from_scale(scale, min_scale, max_scale);\n",
       "    position += delta_position;\n",
       "    scale = scale_from_slider_position(position, min_scale, max_scale);\n",
       "    set_zoom(root, scale, animate);\n",
       "}\n",
       "\n",
       "var set_zoom = function(root, scale, animate) {\n",
       "    var min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"scale\");\n",
       "    var new_scale = Math.max(min_scale, Math.min(scale, max_scale));\n",
       "    if (animate) {\n",
       "        Snap.animate(\n",
       "            old_scale,\n",
       "            new_scale,\n",
       "            function (new_scale) {\n",
       "                update_plot_scale(root, new_scale);\n",
       "            },\n",
       "            200);\n",
       "    } else {\n",
       "        update_plot_scale(root, new_scale);\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "var update_plot_scale = function(root, new_scale) {\n",
       "    var trans = scale_centered_translation(root, new_scale);\n",
       "    set_plot_pan_zoom(root, trans.x, trans.y, new_scale);\n",
       "\n",
       "    root.selectAll(\".zoomslider_thumb\")\n",
       "        .forEach(function (element, i) {\n",
       "            var min_pos = element.data(\"min_pos\"),\n",
       "                max_pos = element.data(\"max_pos\"),\n",
       "                min_scale = root.data(\"min_scale\"),\n",
       "                max_scale = root.data(\"max_scale\");\n",
       "            var xmid = (min_pos + max_pos) / 2;\n",
       "            var xpos = slider_position_from_scale(new_scale, min_scale, max_scale);\n",
       "            element.transform(new Snap.Matrix().translate(\n",
       "                Math.max(min_pos, Math.min(\n",
       "                         max_pos, min_pos + (max_pos - min_pos) * xpos)) - xmid, 0));\n",
       "    });\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragmove = function(dx, dy, x, y, event) {\n",
       "    var root = this.plotroot();\n",
       "    var min_pos = this.data(\"min_pos\"),\n",
       "        max_pos = this.data(\"max_pos\"),\n",
       "        min_scale = root.data(\"min_scale\"),\n",
       "        max_scale = root.data(\"max_scale\"),\n",
       "        old_scale = root.data(\"old_scale\");\n",
       "\n",
       "    var px_per_mm = root.data(\"px_per_mm\");\n",
       "    dx /= px_per_mm;\n",
       "    dy /= px_per_mm;\n",
       "\n",
       "    var xmid = (min_pos + max_pos) / 2;\n",
       "    var xpos = slider_position_from_scale(old_scale, min_scale, max_scale) +\n",
       "                   dx / (max_pos - min_pos);\n",
       "\n",
       "    // compute the new scale\n",
       "    var new_scale = scale_from_slider_position(xpos, min_scale, max_scale);\n",
       "    new_scale = Math.min(max_scale, Math.max(min_scale, new_scale));\n",
       "\n",
       "    update_plot_scale(root, new_scale);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragstart = function(x, y, event) {\n",
       "    this.animate({fill: this.data(\"mouseover_color\")}, 100);\n",
       "    var root = this.plotroot();\n",
       "\n",
       "    // keep track of what the scale was when we started dragging\n",
       "    root.data(\"old_scale\", root.data(\"scale\"));\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.zoomslider_thumb_dragend = function(event) {\n",
       "    this.animate({fill: this.data(\"mouseout_color\")}, 100);\n",
       "    event.stopPropagation();\n",
       "};\n",
       "\n",
       "\n",
       "var toggle_color_class = function(root, color_class, ison) {\n",
       "    var guides = root.selectAll(\".guide.\" + color_class + \",.guide .\" + color_class);\n",
       "    var geoms = root.selectAll(\".geometry.\" + color_class + \",.geometry .\" + color_class);\n",
       "    if (ison) {\n",
       "        guides.animate({opacity: 0.5}, 250);\n",
       "        geoms.animate({opacity: 0.0}, 250);\n",
       "    } else {\n",
       "        guides.animate({opacity: 1.0}, 250);\n",
       "        geoms.animate({opacity: 1.0}, 250);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "Gadfly.colorkey_swatch_click = function(event) {\n",
       "    var root = this.plotroot();\n",
       "    var color_class = this.data(\"color_class\");\n",
       "\n",
       "    if (event.shiftKey) {\n",
       "        root.selectAll(\".colorkey text\")\n",
       "            .forEach(function (element) {\n",
       "                var other_color_class = element.data(\"color_class\");\n",
       "                if (other_color_class != color_class) {\n",
       "                    toggle_color_class(root, other_color_class,\n",
       "                                       element.attr(\"opacity\") == 1.0);\n",
       "                }\n",
       "            });\n",
       "    } else {\n",
       "        toggle_color_class(root, color_class, this.attr(\"opacity\") == 1.0);\n",
       "    }\n",
       "};\n",
       "\n",
       "\n",
       "return Gadfly;\n",
       "\n",
       "}));\n",
       "\n",
       "\n",
       "//@ sourceURL=gadfly.js\n",
       "\n",
       "(function (glob, factory) {\n",
       "    // AMD support\n",
       "      if (typeof require === \"function\" && typeof define === \"function\" && define.amd) {\n",
       "        require([\"Snap.svg\", \"Gadfly\"], function (Snap, Gadfly) {\n",
       "            factory(Snap, Gadfly);\n",
       "        });\n",
       "      } else {\n",
       "          factory(glob.Snap, glob.Gadfly);\n",
       "      }\n",
       "})(window, function (Snap, Gadfly) {\n",
       "    var fig = Snap(\"#img-da3dd3de\");\n",
       "fig.select(\"#img-da3dd3de-5\")\n",
       "   .init_gadfly();\n",
       "fig.select(\"#img-da3dd3de-7\")\n",
       "   .plotroot().data(\"unfocused_ygrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-da3dd3de-7\")\n",
       "   .plotroot().data(\"focused_ygrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-da3dd3de-8\")\n",
       "   .plotroot().data(\"unfocused_xgrid_color\", \"#D0D0E0\")\n",
       ";\n",
       "fig.select(\"#img-da3dd3de-8\")\n",
       "   .plotroot().data(\"focused_xgrid_color\", \"#A0A0A0\")\n",
       ";\n",
       "fig.select(\"#img-da3dd3de-42\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-da3dd3de-42\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-da3dd3de-42\")\n",
       "   .click(Gadfly.zoomslider_zoomin_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "fig.select(\"#img-da3dd3de-44\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-da3dd3de-44\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-da3dd3de-44\")\n",
       "   .click(Gadfly.zoomslider_track_click);\n",
       "fig.select(\"#img-da3dd3de-45\")\n",
       "   .data(\"max_pos\", 120.42)\n",
       ";\n",
       "fig.select(\"#img-da3dd3de-45\")\n",
       "   .data(\"min_pos\", 103.42)\n",
       ";\n",
       "fig.select(\"#img-da3dd3de-45\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-da3dd3de-45\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-da3dd3de-45\")\n",
       "   .drag(Gadfly.zoomslider_thumb_dragmove,\n",
       "     Gadfly.zoomslider_thumb_dragstart,\n",
       "     Gadfly.zoomslider_thumb_dragend)\n",
       ";\n",
       "fig.select(\"#img-da3dd3de-46\")\n",
       "   .data(\"mouseover_color\", \"#CD5C5C\")\n",
       ";\n",
       "fig.select(\"#img-da3dd3de-46\")\n",
       "   .data(\"mouseout_color\", \"#6A6A6A\")\n",
       ";\n",
       "fig.select(\"#img-da3dd3de-46\")\n",
       "   .click(Gadfly.zoomslider_zoomout_click)\n",
       ".mouseenter(Gadfly.zoomslider_button_mouseover)\n",
       ".mouseleave(Gadfly.zoomslider_button_mouseout)\n",
       ";\n",
       "    });\n",
       "]]> </script>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "Plot(...)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m = mean(chn3[:m][100:end])\n",
    "s = mean(chn3[:s][100:end])\n",
    "z = mean(chn3[:z][100:end])\n",
    "n1 = sum(map(z_ -> abs(z_-1) <  abs(z_-2), z))\n",
    "n2 = sum(map(z_ -> abs(z_-1) >= abs(z_-2), z))\n",
    "w = [n1 / 10, n2 / 10]\n",
    "l_simple_g_mean = layer(xintercept=[m...], Geom.vline)\n",
    "l_simple_g = layer([x->w[1] * pdf(Normal(m[1], sqrt(s[1])), x) + w[2] * pdf(Normal(m[2], sqrt(s[2])), x)], -15, 15, Geom.line)\n",
    "l_simple_g_1 = layer([x->w[1] * pdf(Normal(m[1], sqrt(s[1])), x)], -15, 15, Geom.line, Theme(line_style=:dash, default_color=colorant\"springgreen\"))\n",
    "l_simple_g_2 = layer([x->w[1] * pdf(Normal(m[2], sqrt(s[2])), x)], -15, 15, Geom.line, Theme(line_style=:dash, default_color=colorant\"springgreen\"))\n",
    "plot(l_x, l_simple_g_mean, l_simple_g, l_simple_g_1, l_simple_g_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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  "language_info": {
   "file_extension": ".jl",
   "mimetype": "application/julia",
   "name": "julia",
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